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Terrific TDP-43 Talks in Trieste

Wed, 11 Oct 2023 12:58:17 +0000

Terrific TDP-43 Talks in Trieste

As you may know, I am currently a Lady Edith Wolfson Junior Non-Clinical Research Fellow at the University of Cambridge. My work, supported by the MND Association, seeks to develop new tools that enable us to evaluate models of MND we use in the laboratory for research and therapeutic testing. I have been focused on a protein, one of the fundamental building blocks of every cell in our body, which goes rogue in up to 97% of people living with MND. This protein is called TDP-43. It forms clumps (”aggregates”) in specialised brain cells called motor neurons, and is thought to be intimately linked to the death of these cells which underlies all forms of MND.

Recently, I had the privilege of attending the held at the beautiful Stazione Marittima in Trieste, Italy. As the name implies, this meeting was the first of its kind specifically seeking to bring together people from all around the world whose work is focused on TDP-43; from how it is encoded in our DNA, to how the protein is produced, regulated and functions in healthy cells, to how failures of its function can lead to disease. In contrast to traditional meetings focused on a specific disease or cellular phenomenon, there was a uniquely singular focus on TDP-43 and all aspects of its biology.

The meeting was opened by local host Emanuele Buratti. Dr Buratti treated the audience, spanning students to established giants of the field, to a trip down memory lane. Sharing photos of original results and hand-drawn annotations from his lab books from the late 1990’s, Buratti gave early context to a field that has gone on to span more than two decades. It set the scene for a fantastic program featuring presenters from around the globe who would go on to describe novel experimental approaches, advances in our understanding of how TDP-43 relates to MND, and new therapeutic strategies that are gaining traction toward clinical trials. Recounting it all would take longer than the meeting itself (unfortunately a case of ‘you had to be there’!) but I am delighted to have the opportunity to share a snapshot of some of the outstanding science with you.

An early highlight came in the form of a potential new therapeutic strategy, described by James Shorter in his presentation “ (Dis)solving the problem of aberrant protein states“. Recent work from Shorter’s team has focused on the normal function of TDP-43 in cells which involves the separation into a distinct phase, similar to how oil comes together to form droplets in water. If TDP-43 stays in this separated state for too long then it can turn into elongated aggregates similar to those associated with MND. Shorter’s team have , another fundamental cellular building block, to manipulate the phase formed by TDP-43 and reverse the abnormal phases. In theory, this could prevent or even reverse the characteristic clumps formed by TDP-43 in those living with MND - an exciting proof of principle that offers a promising potential new strategy toward viable therapeutics.

Competing for best pop-culture reference, Michael Ward introduced us to the TDP-43 Multiverse during his talk titled “ Functional genomic strategies to identify regulators of neuronal TDP-43 biology”. Just as big data has taken the world by storm, biology is now generating and exploiting bigger datasets than ever before. Ward’s research encourages us to ‘think bigger’ when it comes to TDP-43. Using computational tools, including different cell types and a range of biological molecules such as DNA, RNA and proteins, in an attempt to unravel the chaos that erupts in neurons when TDP-43 function is lost. The resulting data atlas may let us pinpoint the effects of losing TDP-43 function that are specific to motor neurons, a key mechanism of MND that remains unknown.

Late on the second day, Alyssa Coyne presented “ Large scale analysis of sALS and C9orf72 ALS/FTD iPSNs reveals defects in TDP-43 function repaired by genetic therapies”. In essence, a tour de force analysis of the collection of cell models created from people living with MND, which are an invaluable experimental tool. Alyssa asked a simple question, which is similarly at the heart of my research: How good are these models at capturing what we see in real people? One of the principal functions of TDP-43 is in processing RNA. RNA plays a vital role in our cells by converting the instructions from DNA to make proteins. TDP-43 processes a collection of different RNAs, which form a characteristic signature. Looking at the signature in cell models and comparing them to those of the corresponding donor allowed Coyne’s team to establish that signatures are variable between patients, just like fingerprints, but that cells can faithfully recreate the signature of their matched donor. These signatures together pointed toward defects in how molecules move within cells in MND. When TDP-43 is dysfunctional, it is found to move from the DNA storehouse - the nucleus - into the larger cell body, where it forms clumps. , again offering hope of a new potential target for therapeutic intervention.

Last but not least, the poster session — where many early career researchers showcase their work — is always a firm favourite, and this one did not disappoint. With the backdrop of a stunning sunset, attendees were treated to some stellar discussions from the future of the field. Carlo Scialò shared his progress towards the ultrasensitive detection of TDP-43 in nasal swabs; Oscar Wilkins described a new computational tool, SpliceNouveau, to help design next-generation therapies; and Diana Arseni described her groundbreaking work delivering an atomic-scale picture of the shape TDP-43 adopts when it forms the toxic aggregates found in MND. Such sessions are an invaluable opportunity to make connections, discover new technologies, and see ‘fresh-from-the-bench’ science.

In all, this really was a fantastic event spanning all manner of biochemical, biophysical, and clinical approaches to understanding TDP-43, a molecule at the heart of MND. I learnt more than I thought possible and am so grateful for the opportunity to immerse myself in this welcoming and exciting research community. I have no doubt that the collaborations forged throughout the meeting will drive TDP-43 research forward, and I can’t wait for the 2nd conference on TDP-43 function and dysfunction in disease in a few years’ time!

Can’t get enough TDP-43? Find out more about my research , or check out the complete conference program . For anyone interested in the next iteration of the meeting, stay tuned - I look forward to seeing you there!

This post was developed with editorial contributions from Charlotte Roy from the , who supported my attendance at this meeting. A version of the post first appeared .

Toolbox Talk: Notion

Sat, 04 Sep 2021 21:23:03 +0000

Toolbox Talk: Notion

Notion is the type of software that, if you know, you know. After hitting the scene only a few years ago, it has amassed a somewhat cult-like following among personal productivity buffs. For me, Notion is a love affair that started during Melbourne’s extended COVID lockdown in 2020. During this profoundly confronting time, where life seemed beyond control, I found solace in taking control of my tools and systems. A whole new consolidated and streamlined workflow emerged with Notion at its centre - and wow, do I have some thoughts! If you came purely for the Notion nitty-gritty, feel free to skip to the Getting Started section. Otherwise, for Notion newbies, here are a few of my feelings about digital tools for science and how Notion fits the bill for me.

Need a notion about Notion?

First and foremost, Notion is a blank canvas that you can make and mould into (almost) anything! In fact, its versatility is often something sceptics point to as a reason to steer clear. But really, this is where the magic happens. Unfortunately, it also makes Notion incredibly hard to describe! So, here goes.

First: think spreadsheets on steroids. At its core, Notion provides an architecture for building relational databases which are like spreadsheets that can be linked. But, **more than that, each entry itself is a ‘page’ that can contain another database. Which brings me to… Second: think lego! The second aspect of Notion’s design strategy is that all content is considered individual Blocks (even databases). This means that you can stack and link different types of content (from normal text, quotes, callouts, bulleted and numbered lists to more complex structures like embedded webpages, code blocks, equations, date reminders, embedded google drive files, and even databases). Layered on top of this is the ability to display databases as tables, boards, galleries or lists, plus filtering and sorting that makes sure you can see the information you need in the context you need it. Last but not least is the aesthetic! With a simple palette for labelling metadata, headings and text, coupled with optional icons and header images it is super simple to make pretty pages

What we arrive at is a highly versatile and customisable ecosystem that you can use to build and personalise any architecture you need, from a to a to a workplace wiki to a … The possibilities are endless! And for people like me, it presents the opportunity to unify all the disparate digital tools that we had cobbled together to take care of these functions in the past, like Evernote and . In this way, Notion for me embodies the principle of removing friction, by letting me focus on the work without context switching.

A simple sneak peek

In honesty, Notion is sometimes a tool you need to see to understand. So, here is a quick toy task management example. I’ve even provided this page as an template in case you want to try it out!

To start, databases can look just like a regular spreadsheet, but can also be displayed as a board ( think: Trello), list, gallery, timeline or calendar. Here is an example of two databases: “My First Database” viewed as a gallery, and “My Second Database” viewed as a table, placed on a single page titled “Example Relational Databases”. Each column of the table view shows some of the metadata for the individual elements. There are lots of types of metadata you can add, including dates, categories from a dropdown, checkboxes, formulas which calculate a property based on other metadata columns, urls, emails, attachments - so many choices!

Most importantly, we can link these two databases using a relational property, such that we assign Task 1 as associated with Project A. This opens up lots of possibilities, including new formula options called ‘rollups’ which let you see how many tasks for a project are complete.

Now, to this point most of these features you could fandangle out of a spreadsheet if you tried hard enough. But here comes the magic. Each of the entries in the database are themselves pages, which can contain any of the rich content blocks I described above, including more databases. It can also include filtered views of a database so, within a single project, you can overview associated elements.

Last but not least, one of my favourite time-saving functions - templates! You can add templates to any database, such that when you add a new entry to the database it can be prefilled with page content. This is a super-efficient way to capture essential and consistent information for each new entry beyond the metadata options. You can even pre-filter included databases, such that the filtered view automatically includes only related sub-entries.

Ok… But what about Notion for science?

In my 10 years as a scientist, I was not once introduced to the idea of “project management”, much less software fit for the task. It was mostly something that we were inherently supposed to do; keeping track of the overarching aim of our individual project, tracking goals and milestones and tasks. It wasn’t until my first post-doc, when suddenly the number of projects I was involved in exploded, that I found myself reaching for help in the form of digital project management tools.

In contrast, Electronic Lab Notebooks (ELNs) are a digital platform that is slowly permeating all levels of science. The available options seem to be multiplying at a steady rate, and institutional uptake is slowly increasing. Many of the front runner ELNs have connectivity covered, being accessible via browser or app across devices, and provide documentation processes, like versioning and witnessing, in line with funding body and research institution requirements. However, all of the many platforms I have tried suffer from similar issues: (i) they have quite a rigid structure for what constitutes an “experiment”, (ii) data storage size is limited, (iii) structured similarly to a paper notebook which treats experiments as a single entity, not just one of a number of specialised outputs researchers manage and produce, (iv) have no mechanism to track what stage in the experimental process that experiment is in (idea, design, data gathering, data analysis, summary and storage) and (v) are somewhat of an isolated island.

Needless to say, Notion has now alleviated most of these pain points. A few of the best bits:

It works where you do - in an app, browser, mobile, PC, Mac… Wherever you need to be, with synced content meaning everything is always accessible when and where you need it
It is less rigid than Windows file structures, taking full advantage of the interlinked nature of what we do as scientists, building a web of research
Allows you to automate some of the ‘boring’ (although I never find them boring!) organisational bits through templating
Functional web clipper to capture resources and info while you browse
Good selection of commenting, collaboration and automatic versioning features
(Almost) infinite customisability enables you to work in a way that works for you

This being said, there are some important caveats to bear in mind:

Funding bodies sometimes mandate data storage conditions, including the global location of servers for digital data. Notion may not always satisfy this criteria.
Similarly, Notion should not be used for confidential information such as clinical data
Due to the unique nature of Notion’s architecture, there is a limited ability to transfer to alternative systems - however there are substantial backup options to get your data out of Notion if you ever need to
Small number of direct integrations with Google products (like calendar) has been limiting, although the fledgling API will hopefully help this to thrive in the near future.
Some functionality has been slow to materialise - like the ability to natively add symbols outside equations, column-wise formatting within other blocks, and native drawing/writing/pdf annotation (I stick with the Notes app on my iPad, where the export-as-image and copy-as-text functions are my fired)

For me, none of these things were deal-breakers. But certainly, Notion is not fit for every purpose! Buyer beware, as they say.

My Notion Nitty Gritty

For my workspace, I started with the broad buckets of Science, Coding, Communication and Personal. Parallel to this are my Projects, Milestones, Tasks and Resources databases ( think: P.A.R.A.), where individual items are linked to their overarching bucket. From here, filtered views of each of the Project, Milestone and Resource databases form the basis of my daily work ecosystem. I can open a Project page and see each of the Milestones on the go for that project (manuscripts, experiments, funding applications), Resources pertaining to that project (like articles, funding, and ideas), and Tasks for that project (of course sorted by priority and due date). I treat all individual research outputs as Milestones; whether that be a single experiment, a manuscript I’m writing, a presentation I’m giving, a funding application I’m preparing, or a seminar I’ve attended. As well as linked databases, you can also ‘mention’ pages or people inline using the ‘@’ function (almost like a hyperlink) that helps to link together pages to create your very own web of knowledge.

To help with easy access and focusing, I also have a Dashboard page, with some of these @ links to my current priority projects, milestones and tasks - plus a filtered and sorted linked database with some friendly reminders to focus my day!

Some of my other favourite Science databases include my Virtual Lab Book (a filtered version of my Milestones database, which has separate properties for Experiments as they move from conception to data gathering to analysis to writeup), my Reading List (captured as a filtered database from my Resources), and my CV database with which I can filter to produce tailored versions of my CV for individual applications. I have templates set up for different types of Milestones, making it easy to create a new Experiment versus a Manuscript. On the personal front, a sneaky favourite of mine is my recipes database - drool worthy organisation if I do say so myself!

Tips for getting started

If you made it this far, I’m sure you’re thinking “Ok - you sold me. Now, where do I start?”. For many people, staring at the blank screen of a fresh Notion workspace will be quite daunting. If you’ve only ever used out-of-the-box systems, the requirement to create your own from scratch can be overwhelming! However, I truly believe this is where the magic happens. A few tips:

Start with stepping back - the first thing I recommend after installing Notion and creating your first workspace is to close the computer. Yup, put it away and find yourself a pen and paper. First, set to thinking about the broad buckets you want to encapsulate within the workspace. For this process, I found an adaptation of the . method of project management was a great place to start.
Remember to be flexible - your initial workspace should provide some guiding principles to start with, but should be fluid over time as you learn what works, what could be better and, most importantly, what you need. This is the true power of Notion - to grow with you.
Prepare for growing pains - changing to a new system (especially if you are planning a whole-life overhaul like I did!) will invariably present some challenges. But, it will be worth it. Stick with it, and pay attention to the pain points at what you need to adapt.
Face the future - with new systems, the temptation to retrofit your past outputs can be seductive. But (!) you should resist this temptation. Focus instead on ingesting only those things that you currently need into Notion, and leave the rest as the BN (before Notion) archive. You will know where to find things (hopefully) by sticking to the BN and AN line!

Once you have decided what your Notion might look like from a top-down point of view, it’s time to set to work creating the databases and entries that will comprise your workspace. If you’re still struggling with the basics, there are many great tutorials (like from the Notion team) and you can find plenty of inspiration, like and and .

Wrapping up

Wow, what a marathon! In my defence, I warned you I had plenty of feelings when it comes to Notion! My hope is that this post serves as a basic run-through of how I use Notion on a daily basis to capture my research process and enhance my productivity by providing a platform designed and curated by me. Beyond the infrastructure that I provide for myself in Notion, there are a host of strategies I use to link outputs across various other platforms, such that Notion serves as my catch-all and launch point, but I can leave more specialised operations like task management and writing code to specific apps that were tailor-made for those purposes.

In short, Notion may be the broadest tool in my research organisation toolbox, but it is still only a tool that helps bring together other essential tools in the box. You could almost think about it as the toolbelt which keeps all my other tools handy!

That’s all for now. As organisation is intensely personal (what works for you will be very different to what I like and need!), I don’t think it is especially useful to go through my workspace in-depth here. If you’re keen to chat details, make sure to drop me a note on or on the page!

Happy organising 📚

Image credits: via unplash

Year in review: 2020 Edition

Sun, 14 Mar 2021 10:40:50 +0000

Year in review: 2020 Edition

2020 was… A year that felt like a decade, but with the productivity of a boozy long weekend. In case you haven’t been on planet earth for the entire year (hello friend, teach me your secrets), it was of course the year in which a coronavirus (specifically SARS-Cov2) emerged and rapidly took over the globe.

The ensuing pandemonium was slow to build, and even slower to resolve. In fact, most countries around the world are still living with some form of social restrictions aimed at controlling transmission and preventing severe infection. We’ve since entered a recession, predicted by many to be the largest since the global financial crisis. Most importantly, many people lost their lives to the virus, and many more still have a severe and long-lasting illness.

I am fortunate enough to live in a country with very low infection rates and virtually no community transmission, and so life has returned to a post-virus normal. But (of course, there is always a but) to achieve this hefty goal, we as a community endured the longest and harshest lockdown conditions seen anywhere around the globe for almost a year. Make no mistake; it was essential and worthwhile. However, it was also eye-opening, isolating, disruptive and challenging. And as well as being a bench biologist who couldn’t get to the bench, I faced the lockdown separated by state borders from my partner, family and friends. To say it was mentally tough would be a colossal understatement, and despite this I am well aware of many who faced worse than me.

So, in acknowledging that no two experiences of 2020 were alike, I decided to stick with my traditional by-the-numbers account of the past year. You’ll find wins few and far between, more than a handful of losses, and a list of goals that looked a little different from start to finish. Finally, I look to the future and set my sights on recovery in 2021.

Wins

A snapshot of the high points

I survived 2020. I think that certainly belongs in the win column, don’t you?
I read three books, and reviewed one.
I published five blog posts totalling 6500 words, which were viewed 1557 times by 833 different visitors from more than 10 countries
I contributed my first to an online publication
I published my first , providing analysis tools for researchers considering applying for NHMRC funding
I worked over 2500 hours, more than 40% of which went towards submitting my first first-author postdoctoral paper for review to a top-tier journal
Five manuscripts I contributed to were officially published
I slept an average of 7 hours and 5 minutes
I overhauled my entire organisation system, from code to experiments to publications
I created and published not but science-communication videos as part of my first official scicomm training worskhop
I organised and hosted 17 Departmental seminars from a diverse group of researchers spanning career stages and countries - and made a successful transition to virtual when the pandemic hit!
I gave 2 invited seminars, and attended 3 virtual conferences

Losses

A not-so-snappy shot of the low points

Another year with no published first-author manuscripts, despite furiously writing for most of the year
My first-author paper was rejected from 4 different journals before even being sent out for peer review
Almost one fifth of the hours I worked were spent on emails and other administrative tasks
I didn’t write a single grant or application
I downloaded 1084 papers, and read less than 10% of them
I started 4 books that I didn’t finish
I didn’t publish blog posts in 7 out of 12 months
My coding projects are still still in a state of disarray, in desperate need of a tidy and some documentation
I only averaged 3817 steps per day
I was, perhaps, 50% productive on any given day

Lessons

The bits I wish I knew at the start of 2020, but had to learn the hard way.

Selfish isn’t a dirty word - for much of 2020 I struggled with the feeling of being a bad friend, bad partner, bad lab mate, bad family member as I weathered the storm of Victoria’s lockdown alone. I was lonely, unhealthy, unmotivated and struggling to keep my head above water and still I felt uncommitted to the many relationships in my life I let languish during this period. But in reality, I didn’t have anything to give - and I needed to be selfish, to rebuild my own mental health, to redefine my sense of self in this weird and wonderful (?) new world we were suddenly inhabiting. And it took me a long time to be ok with this idea of a self-centred approach to wellbeing. After all, you can’t pour from an empty cup.
Working from home and living at work are two entirely separate things - At the start of 2020 there was an abundance of tips about productive workspaces, setting routines, engaging in your normal ready-for-work activities, setting aside time each day to step away from work…. As someone who has had the luxury of a few work-from-home days in the past that yielded astounding levels of productivity, I was initially optimistic about the opportunities a few onths of working from home presented. It was only a few weeks into what would turn out to be a year long work-from-home order, before I realised how sorely mistaken I was. This was not the quiet, focused time I had enjoyed pre-pandemic, but clouded, overcast and gloomy time spent doom-scrolling, feeling unengaged and unenthusiastic about the prospect of another day spent alone in my home-office. It was a few months in that I came across the phrase living at work, and it struck home how insidiously this transition had happened. Despite having a separate work space, work never really left my home space in the way that I could leave the work office, and I came to realise how important the role of our choice is in this regard.
Variety is the spice of life - Ok, I know this one is a little cliché. And yet, if you’d asked me a year ago I would have adamantly told you that I am a person who is fond of organisation, planning and routines. From breakfast meals to shampoo brands to pens to friends - I am a creature of habit. I know what I like, and I surround myself with it. I structure my time. I plan and organise weeks, months, years in advance and I work toward goals with almost singular focus. And yet, this year almost every single one of those things was thrown completely out the window. It was impossible to plan a week in advance (or even a day sometimes). I found myself missing those spontaneous interruptions to my calendar or walks for coffee with random colleagues during the day. I missed the variety of faces on the tram each morning, and instead sought out variety in walking routes to new cafes for lunch as a poor surrogate. Most vividly I missed the usual spontaneity of a week in bench research science. Normally, each day is subtly different - a different experiment, or technique, this meeting versus that meeting, a new piece of code to work on or a new manuscript to write. Instead of this variety, life became a blur of zoom meetings, trudging forward on a single manuscript, and trying desperately to halt my doom-scrolling as we awaited daily case numbers and press conferences. I will never again take for granted the motivation a varied work day brings to my passion for science.

Goals

As with much about 2020, my goals unfortunately went promptly out the window around June. Even still, I finally submitted the first of three first-author postdoctoral research papers, and successfully created a growing community of Happy Hacker scientists who are learning to code. I started semi-regular yoga and implemented a new morning routine focused on engaging mindfully with the day ahead. While my writing here lagged severely, those posts I managed to write and publish are some of those I am most proud of. None of these things went according to plan, and it certainly wasn’t a glamorous insta-worthy road to ticking boxes. And yet, here we are, moving forward ever so slightly. So where to from here?

Papers are paramount. Déjà vu aside, with drafts still floating around in various states of disarray the first half of 2021 demands some serious focus on wrapping up the next two manuscripts. Using structured writing time of at least twenty hours a week, my goal is to have submitted the remaining two manuscripts before starting my next postdoctoral position mid-year. While last year writing sessions were often sidetracked by more ‘pressing’ needs, this year I will plan each session in advance, using calendar entries for accountability and a master task list for assigning goals and tracking progress.
Revamp the reading routine. Last year I hinted at a timely review of how I consume scientific literature. I’ve often pushed reading to the end of my to-do list and settled for skimming daily email alerts or saving an article or two from Twitter with some handwavy expectation of actually reading them. Instead, I want to not only find time for an engaged reading practice but also give myself space to really think about what I am reading, parlaying this into more (and better!) scientific insights. I will implement two reading sessions per week, drawing pre-selected articles from my ever-growing pile of exciting new material. This will be tracked using a database, which simultaneously enables detailed cross-connection between individual resources and developing insights and ideas within overarching project themes.
Commit to coding cleanup. One of the few positives to come from a year of working from home, coupled with a freshly-submitted manuscript combing computational analyses of wet-lab experiments, was a rapid expansion and solidification of my amateur coding skills. I am often pleasantly surprised when I realise just how far these skills have developed, and it makes me even more excited to pass them on during Hacky Hours each week. And yet, two packages I first wrote more than four years ago still languish, lacking love and in desperate need of refactoring. This is the year I commit to cleaning up these packages. I will spend an hour each week tackling small chucks, which will be tracked using GitHub issues and measured in milestones.
Invest in intentional. Sometimes a week can pass by and I barely realise due to a blur of endless triaging. These type of weeks tend to feel like an old-school cartoon where my wheels are spinning yet the car is going nowhere fast. My goal is to understand (and correct) my balance between the urgent but unimportant tasks that often fill my day (hellloooo email, I’m looking at you…), and the essential but non-urgent tasks that will be of most tangible benefit long term. Beyond task management, I will start each morning by writing down three intentions for the day, using these to anchor how my time is spent and as a record for reflection. I will also frame these intentions within the time management matrix, to ensure I am investing in long term progress by hitting small milestones each and every day.

2020 was without a doubt challenging and confronting and, just between you and I, 2021 was not looking to be off to a great start. After handing over my role in Melbourne and leaping out of my comfort zone, I landed in limbo - awaiting a revised start date for my international Fellowship, unemployed and uncertain of my direction for the first time in over a decade. And yet, here I am daring the universe by setting goals for the year ahead. From here, 2021 is about regrouping, recovering and recalibrating, readying for reentry to the world post-COVID. And I couldn’t be happier to have you along for the ride.

Image credits: @brookelark via

Learning to code: it's as easy and as complex as that.

Sun, 05 Jul 2020 15:12:56 +0000

Learning to code: it’s as easy and as complex as that.

Many life scientists have used their time under pandemic-induced lockdown to learn their first programming language. Yay! Coding has many many advantages (reproducibility, more complex analyses, reusability, time-saving) that I have espoused all too many times before.

Many people start with a tutorial or two, then jump straight in and analyse a dataset. They get a plot, maybe a few statistics and voila! They are now scientists who can code.

Kinda.

See, the thing is there is more (much more) to implementing programmatic workflows in a biological context. Unfortunately, these are the skills that intro-to-programming courses often fail to teach you (or sometimes even mention) - but without them, adding scripts to your workflow can often make your work less reproducible, not more. For the sake of the argument, lets pick one.

Version control.

Imagine a bowl of spaghetti (lots of lines of code), which you admire briefly before throwing at a canvas (your interpreter). You create a beautiful work of art (your plot), and stand back to admire your handiwork. Maybe you show it to a few friends, and they are super impressed. (Awesome!). And then they ask - how did you do it? Not just the throwing motion, or the rough distance between the bowl and the canvas. They want to know the precise location of every single strand of spaghetti in the bowl before you threw it at the canvas. They want to know the recipe you used for the sauce, down to the precise number of grams of oregano.

Now, of course, we aren’t actually talking about a bowl of spaghetti - we are talking about your code. So - of course - you can simply show them the script! Huzzah! The precise instructions that enabled you to make that very specific plot. But here’s the kicker. The code is not static. In fact, chances are that you poured over it for hours (maybe days) adjusting, tweaking, changing, testing and rerunning - all to get the glorious, awe-inspiring plot at the end.

By this stage, you’ve probably made over 100 spaghetti-splattered-spectacles (plots) and your house is starting to smell like an Italian Pizza joint. If I asked you to produce the exact recipe, down to the very position of each strand of spaghetti, for plot number 47 - could you do it?

My guess is probably no.

Conducting experiments is at the heart of science. However, without the essential extracurricular activities like maintaining backups, organising your results files and optimising project management systems, you wouldn’t last very long in academic research. The same is true of coding. Learning to write a functioning script is just the tip of the iceberg when it comes to implementing reproducible computing workflows in biology.

So, with this in mind, what are those all important skills you ask? Well, luckily, far more experienced scholars than I have written on this topic and provided guides (like and ) for those starting out in the computational space. These are highly applicable to biologists learning to code, and I encourage you to check them out before you stray too far down the spaghetti-on-the-wall path (like I did). As with any system, it is easiest to implement new routines before you have become to set in the old ones! At the very least, here are a few things to consider:

, including Github/GitLab/BitBucket
, including efficient folder layouts
and docker containers
practices
, including repositories and citing software you use

For more, make sure you check out the resources below.

Oh, and one last thing.

Unfortunately, this type of organisational work is not typically measured as a key performance outcome for biologists. Your number of git repositories or test coverage for an analysis suite is unlikely to come up in an award nomination or promotion application. And yet, it is entirely crucial as we move toward bigger and more complicated data and analyses - and so I encourage you to take the time to learn anyway. Maybe one day it will be recognised as essential work by the powers that be - but until then, at the very least, it remains essential for anyone wanting to do good reproducible science. And who doesn’t want that?

Final thoughts

So you want to learn to code? Yes - do it, 100%. I honestly couldn’t recommend or encourage it more. But please do so mindfully. If you want to have the best possible chance of integrating this wonderful tool into your scientific ecosystem in the long-term, you have to lay solid foundations and develop sustainable practice/methods.

Have you used any of these techniques as a budding bench-to-bytes biologist? Find me on or head over to the to tell me more!

Resources:

Image credits: Tomwsulcer via & olamishchenko via

A year in review: 2019 edition

Fri, 31 Jan 2020 12:46:00 +0000

The holiday season is a time of reflection for many, me included. However, this was heightened this year, and somewhat hijacked, by the looming start of a new decade.

While there are plenty of discussions of why 2019 isn’t the end of the decade (like , and ), it did little to stem the tide of ten-year progress reports flooding . These outpourings of academic (and personal) success are often incredible and inspirational, but can also be overwhelming and disheartening for those of us who feel less accomplished.

So as is tradition, I decided to stick with my by-the-numbers account of the past year. You’ll find some wins, a handful of losses, and a few goals that looked a little different from start to finish. Finally, I look to the future and set my sights on kicking brand new goals in 2020.

Wins

A snapshot of the high points

I contributed to 4 manuscripts, of which 3 were posted as preprints
I completed my first independently-funded research project using funds totalling $40 000
I was awarded ~ $10 000 in travel awards
I attended 4 national and 2 international conferences
I presented 5 research talks, 2 posters and chaired an academic career development panel
I gave my first invited research seminar at my alma matta
I was awarded an international post-doctoral fellowship (!)
I performed over 45 (mostly week-long) experiments in just 159 working days, and over 75% of these gave useable results
I wrote or edited over 30 000 lines of code
I was an active member of 4 conference and professional committees, and an ordinary member of 4 professional societies
I directly supervised 3 students and informally mentored at least 4 others
I attended a 5-day leadership course, making 5 new connections that have blossomed into 3 new collaborative relationships
I accounted for each of my working days by posting a reflection to a purpose-built Instagram profile, receiving a total of 3191 likes
I authored 10 blog posts containing a total of 14 642 words, which received 5437 views from 3849 visitors across 36 different countries - more than half of these views were on a single post after I shared it with the Twitterverse!
I slept an average of 7 hours a night, did an average 6260 steps per day, and lost 12 kilograms
I read 1 1/2 more books than last year and completed 1/4 of my first ever attempt at cross stitch
I gave my very first tech talk at a local meetup group
I travelled to 3 countries and explored 5 new cities, and took 2571 photos
I spent 365 days being a partner, sister, colleague and friend - being a happy, (mostly!) healthy human

Losses

A snappier shot of the low points

Only one manuscript made it through the review process to be published
None of my first-author manuscripts are any closer to being submitted
Of the 431 papers I downloaded, I read less than 10% of them in full
I am not proud of my ‘bedside manner’, as I was impatient and frequently frustrated with students
I spent over 50 hours preparing 5 unsuccessful grant or fellowship applications
My coding projects are still in a state of disarray, in desperate need of a tidy and some documentation
I only read 3 1/2 books and put 12 kilograms back on
There were days where I barely slept 4 hours and struggled to make 1000 steps
I only took 11 days of leave, and was fuelled by stress and anxiety far more often than passion and curiosity

Lessons

The bits I wish I knew at the start of 2019, but had to learn the hard way.

You have to crawl before you can walk - academic conferences are great, especially the chance to travel internationally. However, you have to have the time and effort already committed to a project to have something new and interesting to present, and in turn to make the most out of the experience.
Time tracking - the more you know! There are already people using your personal data to sell you shoes and expensive holidays - why not use your personal data for good, not evil? Late in 2019, I started tracking how I spend my workday (keep an eye out for more details coming soon!), helping me refocus on my goals, dedicate productive time to important work and better plan my time for specific activities according to how long it had taken in the past.
The sunk-cost fallacy - Sometimes you have to cut your losses and move on, despite having invested so much time and effort and energy into one particular thing. If it’s not right, or not happening, maybe it never will be. And that’s ok - sometimes you have to empty some space to leave room for the next great thing, whether that’s the next big experiment or project, or the next townhouse or friendship. However…
Perseverance is key - every application makes your next application better. Although, being privileged enough to be able to persevere is a huge source of diversity challenge in academia. Appreciate when you have the option to continue chasing a dream, and not just when that dream becomes reality.
Decisions are hard - and making them can change the course of your life immediately, even in how you feel about the people around you.
Some people will never understand - and that’s on them, not you. Living your best life is unlikely to please everyone, so live a life you’re proud of and whether others understand your path or not is irrelevant.

Goals

This time last year I set some goals. This was a new approach to goal-setting for me, and I’m pleased that it worked (moderately) well! Physical activity was a consistent focus - even if only a short walk in the afternoon, I was conscious of the link between how my brain and body feel. I made substantial progress on building reflective practices and, last but not least, I landed the next job!

Building on this foundation, here are my goals for 2020

1. Papers are paramount. With a looming international move, I have a little over six months to tie-up all my projects and get my first-author manuscripts over the line. My goal is to finalise three publication-ready first-author manuscripts by April. With drafts floating around in various states of disarray, I will use structured writing time for at least eight hours a week to make focused progress. I will use calendar entries for accountability and maintain a master task list for tracking progress. I would also like to reorganise my reading and writing process and systems, but that’s a goal for another time!

2. Hacking hand-over. Part of the leadership course I attended encouraged us to think about ourselves as changemakers. This could result from our science, or more broadly our leadership, but nonetheless we were to imagine what change we wanted to make in the world over the next year. Then we had to plan it. Who would we connect with? What skills/tools did we need? I have always been a passionate advocate for programming for life scientists, and I would love to be the catalyst for this in our institute - to take the plan I sketched on paper (yes - real-life butchers paper!) and put it into action. My goal is to establish a local hacky hour at my institute, bringing together experienced, amateur and coding-curious researchers in a collaborative space to learn from each other. I will gather a small working group of researchers experienced in programming by the end of February, where we will brainstorm the best structure, location and time for meetups. The action items from that meeting will serve as a task list for tracking progress, and I will coordinate at least three hacky hours before handing over the reins when I move.

3. Blog better. Despite averaging one post per month last year, I felt there was a lack of substance with so many conference wrapups and few useful, practical or probative posts. The one obvious exception was a rather popular commentary on the state of NHMRC Investigator Grants. This was a combination of an important issue and a good coding project, and I would love to produce more content like this in the future. My goal is to continue posting at least once per month, of which half will pursue practical or probative themes. This will be easily tracked by my posting record here, so feel free to help me stay accountable!

4. Healthy is happy, and mindfulness matters. As I approach another decade of life (that’s right, a big three-oh this year), I am starting to appreciate that a healthy body and mind is not really something you can achieve. There is no box to tick to say you are done, and there isn’t really a finish line. A commitment to maintaining your physical and psychological health is lifelong, and relapses will happen when you aren’t paying attention. My goal is to recover my healthy habits, focusing on yoga and reflections once a week. My progress will be easily tracked by my health app (thanks technology!), and I will continue to maintain my purpose-built Instagram account with weekly posts. For the safety of me and my lab mates, that account will stay anonymous - but it serves as a neat record for me at least!

2019 was undoubtedly one of the hardest, but most rewarding years yet. Just when I finally felt comfortable in my space and role in Melbourne, I landed an international Fellowship - a huge win that is equal parts exciting and terrifying. As they say, life begins at the edge of your comfort zone. So here’s to an adventurous, unknown 2020 - may it be filled with science, self-exploration and smiles.

Image credits: @brookelark via

Book Review: Spineless

Thu, 30 May 2019 12:27:33 +0000

I know, I know, book reviews are so seventh grade. But I am making a conscious effort, both to read more and to actively engage with the media I consume. So, I thought writing down a few tid bits about each of the books I conquer this year might help me and promote some great popular science literature that I think everyone should get around!

The nitty-gritty details:

Title: Spineless: The Science of Jellyfish and the Art of Growing a Backbone

Author: Juli Berwald

Theme:

Jellyfish, general scientific concepts, academia and beyond, motherhood, self-discovery

Target audience:

Everyone

Overall thoughts:

Part travelogue, part memoir, part deep-dive (literally) into the world of jellyfish… Spineless should serve as inspiration for all of us to advocate for research and understanding of the current climate emergency from the perspective of our gelatenous sea-bound dinosaurs. Masterfully intertwined with recounts of her international jelly-finding adventures are details of Berwald’s quest to reclaim a creative space in the midst of family life.

We may span different generations, geographical locations and scientific fields - but I felt an undeniable sense of commeradery and connection with the sentiments throughout this book. Many times along the way I found myself grateful that there was someone else with shared experiences of academia. I also found comfort in the seeming inevitability of her attraction to science. It was so incredible to hear how one person can navigate the complicated spiderweb of academia to pursue a true thirst for knowledge.

Overall, this was a fascinating read for scientists and non-scientists alike. Contemporary, lighthearted and enlightening with amazing illustrations to boot.

**Some of the best bits*:**

What is clear is that the more we learn about these animals from our deep past, the more we will understand about the gnarled evolutionary tree that supports all the animals in the world, including ourselves.

pg 82

As my kids progressed through elementary school, jellyfish had become my own alternative school, a place where my mind could play, and explore, and expand, the intellectual playground that I craved.

pg 84

Gene mutation is always seeking diversity, coming up with innovation, pushing boundaries.

pg 85

… asked him why so many jellyfish were transparent. He looked at me as if I’d asked him why grasshoppers were green. The question is, why isn’t everything transparent?

pg 96

Passion pushes our curiousity, drives innovation, and breaks through boundaries. Economics makes rules, sets boundaries, and forces compromise.

pg 101

While we usually think of domestivation in terms of animals and plants, GFP has essentially become a domesticated gene. By being so useful to us, this single gene has circled the globe, transferred from petri dish in one lab to cell culture in another to your neighbourhood pet store.

pg 118

… your orientation in the world is one of the most important things you can know.

pg 127

There’s something very democratic and modern about this multiple-pacemaker arrangement, evolutionarily ancient as it may be. It is a completely diffuse yet incredibly functional system. The jellyfish’s nervous system is smart without being consolidated.

pg 136

The more we think the same thought, the more neurotransmitters and receptors we produce at that synapse. And so it goes until the memory’s physical structure is a robust synapse, connected by the flood of neurotransmitters and a field of receptors.

pg 140

“information isn’t knowledge; knowledge isn’t wisdom”

pg 156

We have to move beyond this age of combustion… The jellyfish are an alarm that says we are mismanaging our ecosystem. They are a symptom. The cause is our stupid behaviour. And there is nothing else.

pg 161

Given the mighty forces that drive our planet - volcanism, plate techtonics, magnetic storms - … our penchant for focusing on small issues
\[is\]
infuriating. “The planet isn’t going anywhere … We are. Pack your bags.”

pg 161

Even though I was miserable, the decision to quit academics came with a considerable amount of guilt. The scientific community had made an investment of nearly a decade in me. It had pair me, albeit frugally, during my training. And I walked away from it. A piece of me always felt that I left a debt unpaid.

pg 167

The low points - not the moments of joy - were the decisive moments in my life. I had almost never made a change when things were going well.

pg 177

This wasn’t about being capable; it was about being willing. Making a difference would require our collective intention and effort. It would mean growing a spine.

pg 179

You know, maybe that’s where the hope lies. The recognition that we are all stuck here on this planet together. Maybe that fact will be what eventually gets us to clean up our act.

pg 210

My fear wasn’t something I would have admitted in my grad school days when I was trying to show that I could handle anything, that I had what it took, or what I thought it l=took, to be a scientist.

pg 216

Jellyfish had become a better-late-than-never vehicle for me to explore the threats to the ocean’s future. They’re a way to start a conversation about things tha can seem boring and abstract - acidification, warming, overfishing, and coastal development - but that are changing our oceans in fundamental ways.

pg 223

Experiencing the ocean’s brilliance first hand meant more than all my after-school lectures combined… Our kids need to understand what’s at stake too.

pg 278

The realisation that scientists need to roll down their sleeves and button up their jackets has dawned on the European scientists I met much more insistently than it has on those on the other side of the Atlantic.

pg 284

In the United States as well as Europe, there is an ongoing attack on science, a willful insertion of misconception into the public sphere. And that leads to policies that fly in the face of the data and reason.

pg 284

Letters to the editor, which seem such an archaic form of free speech in these Twittering times, actually get read in Washington.

pg 285

Raise your voice. By staying quiet, we are deceiving the public. The public deserves to know what’s going on in the ocean. We are being willfully myopic.

pg 287

If any of those things had happened differently, I wouldn’t be standing in this spot at this moment. Life may be a series of happy accidents, but I had never before had them all come together in one morning.

pg 290

Our dancing turns to fighting, often for the wrong reasons. We fall in love easily, but often with things that don’t matter or even harm us, things that numb us to the thousands of ever-more discernible darts we are shooting at our own planet. This can lead to terrible mistakes, even self-destruction.

pg 304

*Please note these are direct quotes from the reviewed material and do not represent independently conceived ideas.

Handy links:

Buy the book
Check out Bradshaw’s blog

Have you read Spineless, or have another science-adjacent book you can recommend? Find me on or head over to the to tell me more!

Image credits: Spineless cover photo

Toolbox Talk: Storing data using HDF5 files

Sun, 28 Apr 2019 05:43:45 +0000

As an early-career researcher, I am still figuring out the best way to get stuff done. Every day it seems as though my to-do list gets longer and longer, for every item I tick off two more take its place and I have no doubt it will only get worse. I am all about finding the best, most efficient and connected technologies to help alleviate some unnecessary legwork. I have decided to write more on the programs, apps and integrations that I use every day in this Toolbox series. This post focuses on how I store and organise the currency of science: big data!

Data: the invisible bits and bytes of modern life.

Data is an invisible and yet fundamental driver of our digital life in 2019, and the amount of data worldwide is growing every single day. In fact, the International Data Corporation (IDC) estimates the amount of data in the world will grow from an estimated 33 zettabytes (one zettabyte is equivalent to a trillion gigabytes) in 2018 to 175 zettabytes by 2025, an almost unfathomable amount of bits and bytes. Every industry is grappling with the growing mountain of data, and science is no different. Scientists use data as the fuel that powers insight, discovery, and innovation. This demands new infrastructure from the institutes in which we gather data; but it also demands new approaches to the way we as scientists collect, store and analyse data.

During the first five years of my university career, everything I needed for my degree fit safely on a single 16 GB USB stick. Then I went and learnt how to do single-molecule microscopy during the second year of my PhD, and suddenly I was generating 16 GB of data in a single experiment. To cope with this rapid explosion, I invested in the hardware needed to store this data as text or csv files and stumbled my way through establishing a folder-based filing system.

It was during this stint early in my PhD that I first got a taste of programming to deal with this data (for more, check out some of my other programming posts ), however, this still centred on csv/text files for importing data, calculating results, and exporting the final findings. This meant that the data along the way, including input, intermediate and final files, could still be opened by easily-human-readable programs such as Microsoft Excel, and kept supervisors/collaborators without programming experience comfortable.

Recently, this storage pattern was no longer adequate for the size of results I was dealing with. Enter: HDF5 format. If you’ve never heard of this format before, it’s somewhat similar to an Excel document, without the proprietary software tag. Read on for more about what it is, why it’s useful for those dealing with large datasets and how I implemented a storage workflow in HDF5 format using python.

What on earth is HDF5?

Heirarchical Data Format (HDF) is a collection of file formats designed to store large amounts of data in an organised manner. Similar to the way .txt refers to text files or .pdf refers to Portable Document Format files, HDF files are adorned with .hdf, .hdf5, .h5 style extensions. The ongoing development and accessibility of the HDF file format is maintained by the non-profit organisation “The HDF Group”, meaning the tools to store and use HDF files will never rely on proprietary (and often expensive!) software.

More specifically, HDF5 files consist of Datasets that can store arrays of data (think individual sheets in an Excel document), Groups which can store datasets or other groups (think a folder of Excel documents, or folders of folders), and metadata consisting of mapped key-value pairs for attributes of the data (think a detailed description notes page for each sheet/document).

Pros and Cons of the HDF5 format

As with anything, there are good bits and bad bytes about using HDF5 to store data.

Some of the Cons:

Unable to easily open HDF5 with excel or notepad (although there are some being developed that could help overcome this)
No inbuilt calculation or manipulation options
Not readily used by many researchers in the life sciences, including many senior researchers making it difficult to share data with collaborators unfamiliar with the format

A few of the Pros:

Heirarchical format allows for logically storing data in a single file with folder-like architechture
Allows pre-processed data, such as date-time data, to be stored efficiently without loosing the effect of preprocessing (as would otherwise happen in .csv format)
Fast. Compared to other file formats, reading and writing HDF5 files is speedy. For example, writing to HDF5 is 16 times faster than to simple csv file, not to mention the extra overhead that comes from Excel documents. For a comparison to other common formats, check out the
Storing metadata within the file architechture makes sure that these attributes are accessible to anyone wanting/needing to access this data at a later date, and doesn’t rely on the bundling of additional “description” files to make sense of all the parameters and conditions under which the data was collected.
There are advanced options to create datasets that can be edited (rows added etc), and those that are read-only. This is provides an extra level of flexibility that allows, for example, intermediate datasets to be appended to making sure the raw data is not inadvertantly changed.

Sounds great.. But how do I use HDF5 files?

If you have no experience with programming, to get started you can download , which is freeware available from the HDF Group that will allow you to open and edit HDF5 files. In the interest of full disclosure, I have never used this software but it seems to work similarly to graphical user interfaces like Excel (without the price tag!).

If you have a programming language of choice, chances are there are - my tool of choice is of course Python! Even within python, however, there are a few choices for how to interface with the HDF5 machinery. Given that I use Pandas most often for data wrangling, it makes sense to leverage Pandas’ built in support. This includes methods that allows dataframes to be written to directly to HDF5 files using a method provided by the dataframe itself:

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]}, index=['a', 'b', 'c'])
df.to_hdf('data_filename.h5', key='Key_1', mode='w')

This method also allows another object to be written to the same file, with a second key ’s':

s = pd.Series([1, 2, 3, 4])
s.to_hdf('data_filename.h5', key='Key_2')

In this case, the heirarchy is quite simple: two datasets are stored under the single file. To get your data back, it is simple to then read back into a dataframe:

new_df = pd.read_hdf('data_filename.h5', 'Key_1')

For storing multiple files in this manner (i.e. using key-dataframe pairs), I have created a utility function using the HDFStore module (another interface provided by Pandas) that collects dataframes that have been loaded into a dictionary, then saves them to a single HDF5 file:

def dict_to_h5(filename, dictionary, **kwargs):
 store = pd.HDFStore(filename)
 for key, df in dictionary.items():
 store.put(key, df)
 store.get_storer(key).attrs.metadata = kwargs
 store.close()

NB: using the HDFStore in Pandas requires PyTables v3.0.0 or higher. To update your existing Tables installation run the ``pip install –upgrade tables``` command in your terminal.

These are both simple examples in which there is a ‘flat’ data storage pattern. This is great for storing a few large dataframes, or sequentially processed intermediate dataframes for a single result. In most cases, however, you will find it useful to introduce an additional level of hierarchical organisation similar to the folder storage system we are familiar with from OS interfaces. To do this, the keys should have a file-path structure which lists the group hierarchy that the dataset is to be added to. For example:

hdf =HDFStore('storage.h5')
hdf.put('tables/t1',DataFrame(np.random.rand(20,5)))
hdf.put('tables/t2',DataFrame(np.random.rand(10,3)))
hdf.put('new_tables/t1',DataFrame(np.random.rand(15,2)))

This will yeild the following data structure within the single HDF5 file:

/new_tables/t1 frame (shape->[15,2])
/tables/t1 frame (shape->[20,5])
/tables/t2 frame (shape->[10,3])

Python also has other packages specifically for HDF5 manipulation, which have a few more specialised tools. If you’d like to know more about these packages, or how to generate more complicated heirarchies, check out the list of resources below.

A few final thoughts.

Data is a part of life as a scientist, and as life scientists we must strive for better, more versatile approaches to storing and handling the ever-growing datasets produced by our experiments. For me, HDF5 has provided a simple and elegant way to interface with my data. It allows me to store raw and computationally-expensive intermediate ‘checkpoints’, and also means that I can maintain a single HDF5 file that combines data and metadata in a single place. The barrier to entry is quite low, and there are plenty of versatile ways to access data stored in HDF format.

Resources

A to HDF5 with Pandas
You can find additional utitility functions that make it simple to create and store HDF5 files for my projects in my package on GitHub.
For more complicated heirarchies, check out
Some other Python HDF utilities include , for which there are some great on how to generate structured heirarchies.

Do you have a favourite way to store, access and manipulate large datasets? Get in touch on and let me know!

Banner image credit: @ gabons via unsplash

EMBL Proteomics in Health and Disease Mechanisms 2019

Sun, 24 Mar 2019 07:19:06 +0000

Last year I had the privilege and pleasure to attend (and present at) four scientific conferences. This year is shaping up to be just as wonderful, as I have been lucky enough to attend two conferences is as many months, marking the start of what I hope to be a productive year ahead. Here is a little about my recent European adventures, including my first oral presentation at an international conference.

Conference details:

Title:

Date: 7th - 9th March 2019

Location: Heidelberg, Germany

Overview:

Focused on the application of proteomics to cell biology and unraveling disease mechanisms by addressing conceptually novel ways to study long-standing questions in these fields. As most proteomics-based conferences tend to focus on analytical chemistry, the selection of biological topics is usually uneven. Therefore, this unique conference aims to showcase biology applications and build bridges to the disciplines where the technology’s promise is still not nearly fully realised.

There’s a first time for everything!

This was my first truly international conference. What do I mean by that? I have attended and presented at several Australian national conferences consisting of international speakers, but was yet to have travelled overseas to visit a conference in another country. Unfortunately, our isolation makes such an undertaking on a student or starting post-doctoral salary near impossible. In this case, I had been madly applying for every pot of travel funding I could find for the last year, and in a fantastic “it-never-rains-but-it-pours” moment I received all three of the grants I applied for! This meant I was able not only to travel halfway around the world and attend a pre-eminent conference in my field, I could also afford to visit some long-term collaborators for a week afterwards. All together, the two weeks of travel were almost entirely covered and this meant that instead of being consumed with the cost of my every move I could actually focus on the science.

Overall scientific programme and conference feel

Not only did I get to hear about all the amazing developments at the forefront of proteomics research worldwide, I also got to showcase some of my work to leaders in the field. This was an incredible opportunity, and while I was a little disappointed with my talk (owing to sub-optimal preparation and a large dose of nerves), I received overall positive feedback. As well as this, there was so many advances in techniques and biological understanding that I would have never come across on my own, at least not within the next 12 months while the papers are being sucked down the peer-review black hole!

As well as a stunning program, I feel I must give a bonus shout out to the EMBL organising team. Everything ran smoothly, was well organised and timed, and was superbly catered. There was also a small enough number of participants and a well-balanced program between students, post-doctoral researchers, principle investigators and moguls of the field. A conference I would highly recommend to anyone interested in the biological applications of advanced proteomics techniques.

So conferences are just an excuse to travel?

Conferences are the life-blood of academic knowledge sharing. You might think the enormous volume of published literature would be the best source of the up-to-date goings-on of the science world, but sadly in most circumstances you’d be wrong.

I have written before about the importance of conferences, particularly for those of us a little isolated outside the major American and European science hubs. This is because these conferences are essential for establishing and maintaining connections with colleagues, and for hearing about the cutting edge research being done in your field all over the world. As I alluded to above, unfortunately by the time most manuscripts have made it through the academic publishing process, six to twelve months have past (sometimes more) and there are more new and exciting developments already happening (with the advent of preprint servers such as BioRxiv this will hopefully change, but more on that in a later post).

For these reasons, conference attendance in particular for early-career researchers, is about so much more than the travel. Sure, it helps if the places you are visiting are enticing and if you can spare a few days afterward to explore, but the invaluable aspects of conference attendance always take precedence.

Lessons learnt

As my first international meeting, I learnt some new lessons about attending (and making the most of) conferences abroad.

1. Multiply your typical organisation time by at least double. International travel, in addition to conference attendance and accommodation, requires a significant investment of time and energy to plan and book a reasonable itinerary.

2. Departure day is not that far away. I realised after madly rushing to finish my slides on the 14 h flight from Australia to my stopover, that I had perhaps underestimated how quickly my departure date would approach. I was so focused on tackling the seemingly all-so-important last minute experiments and meeting with my students to plan their activities while I was away, that the very reason for my trip got pushed to the side. The result was a less-than-flattering performance during my presentation, and a general feeling of exhaustion throughout the conference which dampened my social spirit. Consequently, I did not proactively initiate many interactions with other attendees, and therefore failed to make as many useful contacts as I otherwise could have.

3. Do your research, researcher! This mostly relates to scoping out the program beforehand. Sure, reading the headline speakers you should be able to identify any leaders that would be good to hear from. But more than this - look over the abstracts, and pinpoint those which are relevant, interesting or potentially useful. To assist this process, concurrently search the presenter in PubMed to get a handle on their other research. Unfortunately, an abstract may not do justice to a programme of scientific discovery, however reading the most recent/most cited articles will help you highlight not-to-miss talks. In addition, I got caught out this conference by an invited speaker whose most recent papers have been instrumental in my project design. Unfortunately, I recognised the first author’s name, and not the speaker (who was senior author on the papers in question) and therefore missed an initial opportunity to discuss this work in depth with the driving principle investigator. Having then done my homework, I was able to make this crucial connection.

4. There will be other conferences, but this is a once-in-a-lifetime experience. Sure, there will be uncomfortable moments, especially attending a conference in a foreign country surrounded by unfamiliar languages and faces. But the best in life happens outside your comfort zone. Unfortunately, it took me a significant portion of the short three-day meeting to push my comfortable boundaries, and after the first two days I left feeling as though I had not taken enough advantage of the opportunities a small meeting with superstars-of-the-field presents. I was disappointed in the impression I made over these two days due to my lack of will power to engage in the social activities, and this was compounded by the feeling of responsibility to those who had funded my trip (including the conference organisers, with a very generous stipend). Ultimately, by the end of the conference, I gathered the seeds of a few meaningful connections to chase up by email - and the very important lesson to make more of these meetings in person in future.

Final thoughts

There are plenty of downsides to science (hellloo no job security, poor work-life balance etc) and travelling (long-haul flights, little sleep, $$$) - but conferences provide a great opportunity to combine the best of both. I would thoroughly recommend this conference, or any in the series of , for early-career researchers looking for an excuse to visit Europe and beyond.

Have you attended any other international conferences or EMBL events you can recommend? Find me on or head over to the to tell me more!

Many thanks to the generous funding provided by the Bio21 Institute Post-doctoral Fellows Travel Grant, the University of Melbourne Faculty of Dentistry, Medicine and Health Early-career Researcher Travel Award and the EMBL Corporate Partnership Programme Travel Grant. Without these initiatives, this travel would not have been possible and I am so very grateful for the opportunities provided by these funds both at the conference and beyond.

Image credits: EMBL Conference logo sourced

#LorneProteins2019 & #FASEB2019

Mon, 11 Feb 2019 06:07:09 +0000

If you’ve landed here after checking out my poster or the , welcome. Thanks for stopping by!

I hope you found something interesting or useful, and enjoyed hearing about the work we are doing to develop new tools for measuring proteostasis. If you have any questions, want to know more about what we do, or simply want to get in touch, you can find me on twitter or head over to the page.

Just can’t get enough of the pretty pretty science? You can find details about the work I presented on my poster here. For anyone who wasn’t at these conferences, or didn’t get a chance to say hi, I have included a brief run-down (and tried to skip over most of the gory - boring, technical - details!).

Now - onto the science!

Setting the scene.

Cells have an extensive quality control network responsible for maintaining their molecular machines, including synthesis, folding, degradation and transport

\[1\]

. Collectively, this machinery is known as the proteostasis network. Proteostasis imbalance results in protein misfolding and aggregation, the central molecular signature of neurodegenerative diseases such as Alzheimer’s and Parkinson’s.

We lack knowledge of which proteins in the cell become vulnerable to improper folding during proteostasis imbalance. One measure of protein foldedness is the extent to which a protein can be unfolded thermally or with a chemical denaturant such as urea. Until recently, it has been difficult to track foldedness in cells due to sheer complexity.

To overcome this, this work specifically aimed to:

Devise a chemical biology and proteomics approach to monitor the foldedness of the proteome.
Determine the influence of pharmacological agents that unbalance proteostasis on proteome foldedness.

What is tetraphenylethene maelimide, other than a tongue twister?!

Tetraphenylethene maelimide (TPE-MI) is a dye (tetraphenylethene maelimide) that becomes fluorescent when it binds to reactive thiol residues

\[2\]

. Buried, reactive thiols are the most buried residue of all amino acids in globular (properly folded) proteins. Monitoring the exposure of these thiols using TPE-MI gives us a sensitive way to probe foldedness in complex mixtures.

To test this strategy, we used a purified, well-studied protein - β-lactoglobulin. We know both the sequence and 3D structure of this protein, and its behaviour in a range of denaturants is known. β-lactoglobulin has 5 thiol residues, of which two pairs are bonded and the remaining one (Cys121) is buried in the core of the folded protein. As β-lactoglobulin unfolds in increasing concentrations of denaturant, we get a corresponding increase in TPE-MI fluorescence.

But what about the giant protein soup our cells make, I hear you ask…

While TPE-MI can reliably tell us about the unfolding of a single, purified protein, our cells are jam-packed with thousands of copies of thousands of different proteins. How can we possibly know which proteins TPE-MI is binding to?

Enter: . This revolutionary tool is a workflow based on mass spectrometry which can report back on the composition of complex mixtures - both which proteins are present, and the relative amount of that protein. The basics of this technique are beyond the scope of this post, but if you are looking for more details check out the resources section below

\[3-5\]

. I have included a brief explanation of the method we use below, which relies on isotopically labelling cells in culture before lysing, denaturing and labelling with TPE-MI. Proteins are digested (chopped up) into regular, smaller pieces before analysis via mass spectrometry.

Using custom software, we can identify and quantify protein pieces. Unfortunately, we cannot identify the protein pieces specifically labelled with TPE-MI, but instead we look for the loss of those pieces. We can do this for many many proteins and start to understand the concentration at which specific proteins unfold. We can even start to understand intricacies in unfolding for seperate protein domains, such as in the example below where different reactive thiols give information on specific domains of Hsp70.

How does this help us understand disease mechanisms?

This new method now provides a way to monitor how the stability of proteins (measured how much denaturant it takes to unfold them) changes under conditions of proteostasis impairment that are present in disease. For example, we are now investigating the changes in proteome foldedness when we inhibit hubs of the proteostasis network such as molecular chaperones. How do the proteins that rely on specific molecular chaperones to be folded change when those proteins are no longer active? What if we stop the cell from degrading old proteins? Or from decorating their proteins with extra modifications that mediate structure and activity like phosphorylation? Defects in this machinery are common in neurodegenerative protein aggregation diseases and we now have the tools to start tackling these questions.

References and handy links

Chiti F, Dobson CM (2017) Annu Rev Biochem 86: 27–68.
Chen MZ, Moily NS, Bridgford JL, Wood RJ, Radwan M, Smith TA, Song Z, Tang BZ, Tilley L, Xu X, Reid GE, Pouladi MA, Hong Y, Hatters DM (2017) Nat Commun 8: 1–10.
Lottspeich, F. (2009). In Proteomics (pp. 3-10). Humana Press.
Graves, P. R., & Haystead, T. A. (2002). Microbiology and molecular biology reviews, 66(1), 39-63.

That’s all from me for now. Like the pretty pictures? Still can’t get enough of the science? Simply want to get in touch? Find me on twitter or head over the to page - I’d love to hear from you! Now, back to the beach 🏄🌴☀️ or the snow-covered mountains 🏔️⛷️!

A year in review: 2018 edition

Tue, 15 Jan 2019 09:52:30 +0000

The last few weeks have seen a flood of people posting their 2018 achievements, promoting the academic currency of papers published, grants won, students mentored and conferences attended.

Without taking away from these achievements, I wanted to focus on viewing myself as more than my work, and especially more than the ‘publish or perish’-driven manuscript list. And so, here lives my reflection on the year that was. Lessons remain a crucial part; after all,

“If a man looks at the world when he is 50 the same way he looked at it when he was 20 and it hasn’t changed, then he has wasted 30 years of his life,”

Muhamed Ali

Of course, I would be remiss not to celebrate the high points - but I have tried to temper the ‘gloating’ with a few honest low points. Finally, I take a look to the future. By defining goals which will drive my personal and professional life in 2019, I hope to kick off a fulfilling and smooth-sailing year with the course charted and the wind in my sails.

Wins

A snapshot of the high points

I received my first personal scientific project funding through an Early-Career Researcher Grant
I had four papers published, including the last of my PhD research, and landed travel funds for an international conference
I was priviledged to give too many conference presentations to count (Lornes, ABS-ABA, Winter School..)
I developed and grew this page, with 20 blog posts including tools, conference reviews, book reviews and scicomm
I produced hundreds (maybe thousands?) of lines of brand new code - but more importantly, saw a significant improvement in my ability and confidence when programming which has allowed me to assist others
I attended my first PyLadies meetup, where I met people like me (in science, learning python independently) and some less like me (employed full time in programming or data analysis positions)
I developed closer relationships with family and friends, as I worked harder to maintain and build these ties
I read two more books than last year
I consistently, regularly exercised, losing 15 kilograms
I hit a saving milestone and we bought a house

Losses

A snapier shot of the low points

I worked for two months on experiments that were to resuscitate one of my major projects
I’m now left with no papers in the pipeline, leaving lots for the year ahead to wrap up these projects
My coding projects are in somewhat of a state of disarray, in desperate need of a tidy and some documentation
I only read 2 books, and put 8 kilograms back on
I spent more than 50 hours writing six grants, all of which were unsuccessful
I was quick to judge others and less approachable than I would like to be, letting my stress seep to the outside
We unbought a hous

Lessons

The bits I wish I knew at the start of 2018, but had to learn the hard way

Have the hard conversations - with your boss, your partner, yourself
Self-care is about what you need - not what everyone else’s definition of rest and relaxation tells them (and they, therefore, tell you) you should be doing
“There are less qualified people than you doing what you want to do, just because they decided to believe in themselves. Period.”
Make a positivity folder and actively collect the warm fuzzy moments: emails, photos, messages, compliments, congratulations…
If you want to do something, really want to, then make time. Do it. No one else is going to do it for you, and your schedule will not magically clear. Life is never going to get less hectic or stressful.
Every day, hour, minute you spend wishing your way to the next thing (job, house, friend, partner) you will equally spend wishing you had taken the time to value what you had, to revel in it.
Prioritise, prioritise, prioritise

Goals

Hopefully to help me meander with purpose through 2019

It might be a little meta, but a big goal of mine this year is to learn to set SMART goals. Not so much “new years resolutions” - but personal and professional goals that I would like to work towards every day.
If you’ve never heard of the SMART goal concept, you can find a more detailed description , but in a nutshell SMART goals are:
- S - specific, significant, stretching
- M - measurable, meaningful, motivational
- A - agreed upon, attainable, achievable, acceptable, action-oriented
- R - realistic, relevant, reasonable, rewarding, results-oriented
- T - time-based, time-bound, timely, tangible, trackable
With this in mind, I have the following goals for 2019:
- Yoga at least two days in a fortnite during 2019. A flexible body -> flexible mind -> clarity of ideas, increased alertness and engagement with the task at hand. I would like to be able to better calm my mind when distraction threatens. I will track this goal via a calendar which records each session.
- Land the next job - be strong enough to throw myself into the applications and let go of the guilt of not chasing (limited) Australian funds. This will be measured via my application for at least 3 more Fellowship programs.
- Attitude adjustment - I will track this goal via weekly mini-reflections, where I will focus on (1) Learning to take control of what is within my reach, and to more rapidly accept that which is outside my control and move on, (2) Doing one self-positive task per day - learning, physical activity, kindness, and (3) Fostering self belief to replace self doubt, in personal relationships, professional settings and long-term career prospects
- Prioritise, prioritise, prioritise!

And with that, it’s time to say sayonara 2018 - bring on 2019.

May science be kind to you!

Image credit: @brookelark via

NoBell Prize 2018

Fri, 30 Nov 2018 11:01:39 +0000

The phrase “Nobel Prize” usually evokes a sense of prestige and gravitas. There is no doubt that these prizes are bestowed upon individuals who have made outstanding contributions to the human race. However, sometimes what exactly the prize-winners invention or contribution was can be a little beyond the grasp of your average citizen.

Enter the “NoBell Prize”.

Hosted each year by the Melbourne Neuroscience Institute, this fantastic event is a funny scicomm-athon open to the general public, where brain and mind researchers attempt to explain their research without jargon in three minutes. Should they utter a sceric of technical jargon, the judging panel ring a bell and the researcher must satisfactorily explain the concept in lay terms before moving on. At the end of the night, the number of bell rings is tallied up and the researcher with the least bells is crowned victorious with a ‘prestigous’ faux-gold cup. This year pitted 5 fantastic researchers against the bell:

Dr David Farmer - Research Fellow, Autonomic Neuroscience Laboratory, The Florey Institute
Dr Holly Chinnery - Corneal and Ocular Immunology Unit Lab Director
A/Prof Carsten Murawski- Principal Investigator, Brain Mind and Markets Laboratory
Prof Erica Fletcher - Visual Neuroscience Laboratory Head
Dr Scott Kolbe - Advanced Neuroimaging Laboratory Head

While at face value this may seem like a frivolous take on a serious and distinguished event, in the age of fake news and dismissed scientific evidence the importance of events like these cannot be understated. It was articulated best by the host of the evening, Dr. Shane Huntington, when he espoused the responsibility we have as researchers not only to conduct good science, but to demand good science, to advocate good science, and to communicate good science.

In fact, as Dr. Huntington believes, the current fracturing of truth and lack of belief in evidence-based policy is a reflection of a failure by us as an academic community to effectively engage and communicate with the public. Events like these are essential for both public science literacy and practice in effective communication for researchers.

Even with the serious (and important) aspects, all around the NoBell Prize was a fantastic evening with lots of laughs and an equal helping of learning - even for me! If you have the chance, I highly recommend checking out the NoBell Prize in 2019. Maybe you could even go up against the bells yourself!

Book review: The Effective Scientist

Sun, 28 Oct 2018 10:32:43 +0000

I know, I know, book reviews are so seventh grade. But I am making a conscious effort not only to read more this year, but also to actively engage with the media I consume. So, I thought writing down a few tid bits about each of the books I conquer this year might help me and promote some great popular science literature that I think everyone should get around!

Title: The Effective Scientist

Author: Corey. J. A. Bradshaw

Theme:
ECRs, academia, science impact

Target audience:
ECRs across scientific disciplines

Overall thoughts:
A well written, self-reflective evaluation of the important aspects surrounding scientific research that make or break a scientific career.

As a “first-gen” PhD, I naively thought that being good at the research (understanding concepts, designing and interpreting experiment, analysing data, writing papers and teaching students) would be enough to guarantee me a successful and impactful career in academia. However, very soon into my first post-doc it became clear that there was a great deal more than these qualities required, and that it was not something that is taught in Grad school. Mostly, people garnered “insider knowledge” on how to succeed. With this truthful and frank book, Bradshaw provides some of these insights as a guide for new early career researchers, helping to at least level the playing field for those of us not in the know. So much of his recounts were relatable, and wisdom enlightening. Even those who consider themselves in the know could learn a thing or two from the empathetic approach and good lab-building practice ideas put forward by Bradshaw. Together, these skills may help you survive (maybe even thrive) in the world of academic science, will lead to a more fulfilling and impactful career, and allow you to positively contribute to the betterment of society. And as a side-note, the print version itself is absolutely beautiful (props to Rene Campbell for the images throughout, and for the amazing cover image) - a win-win-win!

Overall, I can not recommend this book enough for early-career scientists of all disciplines. Aspiring post-graduate students, newly-minted PhD’s, post-docs and junior principle investigators alike can all benefit from the wisdom held between this magnificent cover!

Some of the best bits*:

Knowing what or how to achieve what you will be expected to do is not necessarily intuitive or easy

We must compete in an age of on-tap information, most of which is either meaningless drivel or utter nonsense

To most, significant just sounds more authoritative, educated, and erudite than a lot or big. This is, of course, complete rubbish because some people use big words to his the fact that they are not quite as clever as they think they are

…you might be of the mistaken assumption that science is a nice, linear, logical process leading to unambiguous conclusions.

Failure, at least of the temporary kind, is therefore ironically a state that you will necessarily have to get used to if you are to succeed as a scientist.

What lacking novelty really means is ‘we do not think your paper will get as many citations as we would like’.

I could go on and on, but in reality this whole book bears repeating. In fact, I am quite certain that I will return many times over the years to revisit specific chapters or paragraphs - to cherry-pick more than these few phrases does an injustice to the rest, you will simply have to read it!

*Please note these are direct quotes from the reviewed material and do not represent independently conceived ideas.

Handy links:

Buy the book
Check out Bradshaw’s blog

Toolbox talk: Atom, Jupyter and Hydrogen

Sun, 23 Sep 2018 11:47:32 +0000

As an early-career researcher, I am still figuring out the best way to get stuff done. Every day it seems like my to-do list gets longer and longer, for every item I tick off two more take its place and I have no doubt it will only get worse. I am all about finding the best, most efficient and connected technologies to help alleviate some unnecessary legwork. I have decided to write more on the programs, apps and integrations that I use every day in this Toolbox series. This post focuses on what is currently the best (in my humble opinion) hackable text editor for writing, programming and data analysis: Atom!

The basics: Atom as a building block.

Billed as the “hackable text editor for the 21st Century”, is a free, open-source, cross-platform desktop application for editing plain text and source code. While the base program was developed by GitHub, many of best functionalities are community built and maintained under free liscences. This combination of core support and extensibility has resulted in an unparalleled level of customisability, and makes Atom my editor of choice for everything from simple text documents, to data analysis to developing python packages. For coders and non-coders alike, there is something for everyone in the Atom ecosystem.

From an aesthetic point of view, Atom has a nice panelled interface which can be extended at will. Below you can see a standard layout I gravitate towards while I am analysing data. The leftmost pane (the file tree) allows you to open an entire folder or folder tree to easily see all of the files associated with the project you are currently working on, complete with coloured file-type icons for easy visual grepping. In addition, I can have multiple panes open side-by-side which allows me to operate on code/data in one building and document the analysis approach in the second. Finally, to the right is the output/Git pane (more on that later).

An example analysis layout in Atom.

Atom also has a vast array of installable themes to customise the window colour and aesthetic. I myself am partial to a dark theme, with a subdued syntax highlighting (check out the OneDark theme). If you prefer a more traditional light theme, there are plenty of those too!

The best bits: Git(Hub), Integrated Development Environment and Real-time Collaboration functionality

Being built by GitHub, it is fair to expect some level of integration with Git. If you’re not yet familiar with Git, or version control in general, you can read more about it . In short, even if you have never written a single line of code in your life, version control is a must for anyone routinely creating and editing documents of any kind. For now, suffice to say that Git has traditionally been a command-line tool and therefore mildly intimidating to those of us who found it with little experience. Recently, GitHub introduced a which alleviates some of the hassles of interacting with Git via the command line. However, Atom takes this functionality and seamlessly integrates it within the environment where the work is being done. No longer do I need to switch windows to another app or terminal - I can immediately see the documents that have detected changes, stage and commit those changes and push to GitHub from within Atom. More than this, Atom allows you to create and change branches, and push/fetch/pull from remote repositories all without ever having to change windows.

One of the reasons I came to it in the first place was the flexibililty to create an Integrated Development Environment (IDE) for any programming language. An IDE typically provides comprehensive facilities to edit, build and debug source code for a given language. Atom has taken on this task to provide support for a long long list of the most popular languages. This is achieved via installation of community-driven packages - more on this in a little bit.

Finally, Atom provides an interface for real-time collaborative coding. While I am yet to test this functionality, Atom’s “Teletype” promises the ability for users to share their workspace with team members and collaborate on code in real time using a shared portal. If you have used this feature, be sure to let me know how you find it!

Easy extensions: Size may not matter, but it’s all about the package(s)

They don’t call Atom the most hackable text editor for nothing! Although the Git interface is packaged as part of the raw Atom install, many of the other features I’ve already described rely on the installation of community developed and maintained packages. The variety and functionality of these packages is seemingly endless, and installing a new package is as simple as opening the settings view and searching for the package. No matter what language you intend to use Atom for (or even just for general editing of plain text or markdown documents), there are bound to be a few packages that will make life easier.

Given Atom is agnotistic to language, there are plenty of packages for common languages like R, Java, C #…. If any of these is your language of choice, I encourage you to poke around online and see what packages people recommend. For the remainder of this post, I will focus on how I set up Atom as a home for my Python development and data analysis.

Accessorising Atom: a Python perspective

When first learning python, I used Spyder as my development environment. After a while, I got itchy feet and investigated Sublime (another text editor) and was intrigued by it’s customisability. After a brief stint, it wasn’t long before I discovered Atom and, as they say, the rest is history! There are plenty of generic “how-to-set-up-Atom-for-Python” articles (you can find examples and ), so I won’t spend too much time rehashing these here. Suffice to say, there are a few basic packages you will want to install to get the most out of Atom for your python projects. A few examples include:

Perhaps my favourite aspect of Atom (and in fact the reason I know recommend it to everyone I help get started with python) is the easy integration with Jupyter. If you haven’t come across Jupyter yet, Jupyter Notebooks provide an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text in a whole host of languages. Notebooks support over 40 programming languages at the time of writing, including Python, R, Julia….This is managed through the installation of different , and if you are keen to run additional languages then check out how to access different kernels . In the case of python, IPython is the central dependency of Jupyter and thus is preinstalled. Jupyter Notebooks are in and of themselves a great environment for data cleaning and transformation, numerical simulation, statistical modelling, data visualization and much more. However, they require the analysis, version control and file management to be completed in different locations (other windows, apps, etc). Enter . This neat package brings all the functionality of Jupyter notebooks (documentation, in-line plotting and results etc) to your atom environment using the installed kernels. In my opinion, this is a must have for someone getting started with Python in Atom. To get started, follow the installation guide . As a bonus, is an extension package providing variable exploration in beta. If this is an IDE feature you cannot live without, check it out!

Better than basics: integrating python virtual environments

Similar to Git, using virtual environments with Python (despite being important best practice!) can be extremely intimidating for a newbie. Again, having to make and activate virtual environments via the terminal, and keep track of potential leftmost to use, set the bar above what I could digest and integrate into my workflow initially. Without this essential tool, my base install of python became littered with packages, many of which had dependencies that broke other packages. And don’t even get me started on the nightmare that was needing a safe install of both Python 2 and Python 3 for different projects!

Eventually, I got my act together and installed both and . If you need a little more advice, check out these great tutorials from and . For a little while, I was content that I could activate different environments if I desperately needed to - but was not overly inclined to use them on a regular basis! That was until I found the Atom package specifically designed to integrate this functionality: . This package lets you activate different virtual environments from within Atom, and combined with Hydrogen’s kernel manageraesthetic can have complete control of the python environment within which you are trying to run code!

Conclusions

Atom is a great multipurpose ecosystem with huge extensibility to tackle common tasks, both for general text documents and coding projects. There is support in the form of community developed packages, and complete customisability. By combining a few of these packages, it is possible to build a friendly development/analysis environment for those new to coding, or seasoned veterans alike, which encourages best practices at every turn.

That’s all from me for now - happy coding!

Quick Recap: PyLadies Melbourne Event

Tue, 31 Jul 2018 11:24:05 +0000

Locating the labyrinth a nd meeting the meetup For a few months, I had been working on the courage to check out one of the many coding-related groups held all across Melbourne each month. There are the meetups, various networking events and more data science groups than I could possibly list here (if any of these peaks your interest, check out the meetup list ). Still, as a scientist-turned-programmer (and a shy one at that) I wasn’t too quick to jump in the deep end with a roomful of people who of course I assume know everything there is to know about programming. Eventually, an email popped into my inbox with details for an upcoming centered around a tool I had been using (and hating) almost daily, and finally, I thought, “This is it. It’s now or never”. So, a cold Melbourne Monday night I bundled up my backpack and headed into the city after a long day at work.

After a tricky start (getting into locked business buildings in the heart of the Melbourne CBD is not my strong suite - mastermind criminal I am not!), I finally made it to a table jam-packed with Souvas accompanied by a fridge full of beer and cider (or apple juice poppers if that’s what you’re into). I was one of the last to arrive, so I quietly slunk in the back and collected some food before introducing myself to the orchestrator of the event. Not long after a quick round of “What’s your name, what do you do…”, we were bundled through to a second room where there was a bunch of tables and chairs set up around a projector.

For the next 90 minutes, enthralled and entertained with her tales learning python’s premier plotting library, matplotlib. I won’t go too much into the finer details of her talk - you can check it out . But, I will tell you a little about Ash and why her talk being my first foray into python meetups was so important. A masters student come research assistant, Ash is a bench-trained scientist with a flair for uncovering transcriptional signatures of immune genes in cancer. She came into python as the only scientist in her lab using this language and has built analysis pipelines for her work from the ground up. Coming into python as a scientist was definitely something I could relate to! Ash was brutally honest about how hard she found it at times to navigate the various Matplotlib interfaces. She unashamedly admitted how easy it was to spend hours ‘prettifying’ your graphs. And most importantly for me, she had a room full of fellow pythonistas, mostly software engineers and data scientists, nodding along. It was unbelievably reassuring to hear that I wasn’t alone in my experiences of matplotlib-induced pain. On top of that, having someone methodically explain the basic concepts, the tricky syntax and the bizarre labeling conventions was so helpful for crystallising the knowledge I had slowly accumulated over the last year or two since starting to use matplotlib more regularly. I even learned a few new tricks (aspect=‘auto’ anyone??).

I know it may seem like I’m gushing (and maybe I am, a little) but it truly was a revelation to me that scientists could have something so useful and relevant to contribute to what (on the surface) seemed like a simple conversation for those ‘in the know’. The PyLadies are an incredibly welcoming bunch, and I can’t wait for next month to ‘meetup’ with them again.

The nitty gritty When: Third Monday of each month Where: Melbourne CBD Who: Anyone identifying as female who is interested in python. What: The presenters and topics vary by month, so for all the details make sure to check out the PyLadies meetup page.

Note: The details I’ve included here are for the . If this is not near you, don’t dismay - there are PyLadies groups all over the world and most likely one near you! There are even remote PyLadies groups that regularly post talks online if this sounds more like your jam head to check it out.

Python not your thing? There are so, so many different groups on , I am sure you will find something that takes your fancy!

Resources If you’re in a world of matplotlib pain, here are a few of my favourite resources that (along with Ash’s talk) really help to lay out ground rules and will hopefully give you a fighting chance:

Magnified 2018

Tue, 05 Jun 2018 07:53:54 +0000

The Illawarra Health and Medical Research Institute (IHMRI), in association with the School of Arts, English and Media at the University of Wollongong (UOW), are hosting a fundraising exhibition featuring images from the work of researchers and students, in support of Motor Neuron Disease (MND) research at IHMRI. This is a cause quite close to my heart, and as an alumnus, I was lucky enough to be invited to contribute. I actually had a heap of fun choosing my artwork (you can check out my submissions below) and for all the details on when and where you can find the exhibition head . Works in the exhibition will be on sale to the general public, with all proceeds going towards Motor Neuron Disease (MND) research at IHMRI. What better reason do you need to pick up some fantastic sciart?

Decoding Proteostasis

Proteins are the major cellular building blocks fundamental for most basic operations sustaining life. Most proteins need extensive management by the cell’s proteostasis machinery to maintain their proper shape. Proteostasis imbalance can cause neuronal death, leading to neurodegenerative disease. Various cellular stresses, such as inhibiting housekeeping functions or dismantling structural components, can differentially impact neuronal health. Understanding changes in each individual protein (columns) within a cell as it responds to different stresses (rows) highlights how different stress types influence proteostasis. Revealing common vulnerable pathways, by decoding this ‘proteome barcode’, will help focus future therapeutic targeting on neurons weakest links.

The twists and turns of proteostasis

Misfolded proteins aggregate into elongated fibrils (yellow/green ribbons), which cause neuronal death and lead to neurodegenerative diseases like MND, Parkinson’s and Alzheimer’s disease. Using powerful microscopes, we can watch how the molecular chaperones (red), part of the cells proteostasis defence network, attach along the fibrils, helping to protect the neurons from these toxic tentacles.

what to do when you can't get a word in edge ways

Sat, 28 Apr 2018 03:45:17 +0000

I don’t believe in resolutions, mostly because I have finally learnt (after 20-something years) that I will never stick to them. However, January 1st this year saw me looking to make a few key changes in my lifestyle. A few of these resulted from lessons I learnt throughout 2017 (you can read more about those ), and some were personal decisions that I felt would contribute to my mental, professional and physical health. One of those decisions was a commitment to reading and writing more. What you see here is my attempt at writing - but what about reading? I consume a steady stream of media everyday, and I decided it was high time that I put the constant onslaught of information to better use - to make it work for me, instead of feeling like I was drowning under it’s weight. My answer to this challenge came in a few forms:

1. A new system for prioritising and tracking purely scientific reading. This includes journal articles and media pieces with direct relevance to my current project, or project ideas that I hope to pursue one day. For more on my new system, and how I automate some of the process, keep an eye out for a future post coming soon.

2. A more balanced and positive social media environment. For me, this meant migrating to Instagram and Twitter (in favour of Facebook). Given I was a relative late comer to Twitter, I was able to curate my social network to generate an environment filled with positive stories, useful information, scicomm and professional opportunities etc. Not only does my time spent on these social channels no longer feel cumbersome and negative, but I have also found a brand new way to stay up to date with new science and funding opportunities, as well as a group of positive uplifting scientists working to effect real change in the systems they see failing scientists (and particular female scientists) worldwide.

3. A conscious effort to read something for leisure. While I allowed myself to choose books loosely based in science, it had to be in an expanded real-life paperback-in-hand book (no online journal articles) that I would sit with and focus solely on for at least half an hour at a time. I have only managed a single book this year (more on that ), but these ‘unplugged’ moments have helped anchor my self-care for the past few months. I find it refreshing to have a single focus for a defined time period (no electronic attention-grabbing distractions), and it was great to stretch my mind and take in broad science outside my niche that was designed for a popular audience.

After almost four months, my media-rich life is finally beginning to feel manageable. Tackling the barrage of text and images head on, I have found a balance between reading I have to do (articles), reading I am inevitably going to do (socials) and reading I would like to do (books). And if nothing else, this really reinforces for me the biggest lesson of 2017 - call it yin and yang, call it … call it whatever you like - it’s all about the balance!

Book review: Human Universe

Sat, 28 Apr 2018 03:43:15 +0000

I know, I know, book reviews are so seventh grade. But I am making a conscious effort not only to read more this year, but also to actively engaging with the media I consume. So, I thought writing down a few tid bits about each of the books I conquer this year might help me and promote some great popular science literature that I think everyone should get around!

Title: Human Universe Theme:

A self professed love letter to humanity, this book asks questions about our origins, our destiny, and our place in the universe, covering the science behind each scale in the universe, from single cells to whole galaxies to the infinite multiverse.

Target audience:

Inquisitive minds, suitable for both scientists and those with little to no scientific background.

Overall thoughts:

Well crafted stories and arguments, with an appropriate level of context for someone with no background in science, but not so much as to be nauseatingly boring for scientists. In many instances, Cox manages to articulate many of my feelings about science, policy and the challenges we face both as scientists and more broadly as a society with a solid foundation in established scientific research.

Some of the best bits*:

The language of science - because there is no better demonstration of our ascent… than the exponentiation of knowledge
Education powers the mind beyond direct experience - onwards and outwards
Common sense is completely worthless and irrelevant when trying to understand reality
The inbuilt and unavoidable stupidity of intelligent beings
Countries whose borders and interests are defined by imagined local differences and arbitrary religious dogma, both of which are utterly irrelevant and meaningless on a galactic scale
A lovely example of serendipity coupled with curiosity and a sprinkling of genius; from cannonballs to snowflakes to the code of life.
Science is a time machine, and it goes both ways. We are able to predict our future with increasing certainty. Our ability to act in response to these predictions will ultimately determine our fate.
Science and reason make the darkness visible
We woken up at the wheel of a bus and realised we don’t know how to drive it
A common governmental lament is new knowledge is not converted efficiently enough into economic growth. Is that what knowledge is for? Who pays for progress? Who should pay for progress?
there is much research to be done , but the barriers are likely to be budgetary rather than fundamental; the United States spends more on pet grooming than it does on fusion research.
I teach, I am taught, I research and I learn. I have been fortunate.
What are we made of? Up quarks, down quarks and electrons.* Please note these are direct quotes from the reviewed material, and do not represent independently conceived ideas. Where can I find it? Get it online .

the nomadic scientist: blessing or curse?

Thu, 05 Apr 2018 10:36:32 +0000

From the very beginning of my undergraduate degree, I knew that I wanted to pursue research overseas. Not so much a permanent relocation, but I was very keen to leverage the international nature of science to see the world. I secured a post-graduate position with a group leader who was open and supportive of this goal, and was instrumental in helping me go abroad during my PhD research. What followed was a whirlwind trip to Cambridge, UK, where I worked on acquiring a new technique to add to my developing skills arsenal. Despite the short stint, it was hands down the most personally and professionally life changing experience.

This is not to say that my home institute isn’t producing to good science - it is - but through this experience I was immersed in a city bursting at the seams with passionate experts, cutting-edge research and world-leading techniques. To say I fell in love would be an understatement. The cohesiveness and intertwined networks I observed whilst there were an incredible, eyeopening window into the collaboration that comes from bringing together world-leading experts from a broad range of disciplines in a melting pot dedicated to the pursuit of knowledge.

After returning to Australia, I worked towards the holy grail - thesis submission - and dreamed of the postdoctoral jobs I could chase internationally. One year on I am still here, and in a position I am thoroughly enjoying, but you better believe I still have my eye on an overseas position in the next 5 years. I do wholeheartedly believe that a diverse research training period is a critical foundation for a well rounded researcher, giving context and cultivating understanding of the abundant theories and approaches one can take to answer the big scientific questions. Diverse experiences offer the chance to explore the problem at hand from a new perspective, leading to unique insight.

And as excited as I still am about all the places science could take me in the next few chapters, my extra-continental daydreams have been tainted with an air of urgency of late. I am beginning to feel as though, with the current funding climate, the only way I am going to get a foot in the door is to do my time in a country where the pay is less, the work-life balance a little more unbalanced and my family a little(lot) further away. Even worse, I am acutely aware that in this situation I am the privileged one. Assuming I am lucky enough the secure a position in a good lab group in my area of research, I have very few restrictions or barriers to relocation. Sure, money is always an issue. And there might be a few personal hiccups (my partner is not infected with my incurable case of wanderlust), but I am (relatively) young, without kids and with no significant financial constraints (other than the misguided hope to someday get on the property ladder).

Many of my colleagues, and friends, do not enjoy the same level of flexibility.

And so, I suppose this post is more about what you think - is it possible to progress in the Australian scientific research landscape without being a nomad, at least for a little while? And what effect does this have on the diversity retained in the upper echelons of the academic institutions?

lifeguards of the cell

Sun, 11 Mar 2018 09:39:27 +0000

I believe communicating science with a broad and diverse audience is our responsibility as researchers. One of my most important audiences has always been my friends and family, many of whom didn’t do or don’t remember a single high school biology lesson. Needless to say, they’ve been a great testing ground for honing my elevator pitch - and I’ve discovered a neat metaphor makes it so much easier to describe complex scientific concepts without the dumbfounded look that normally accompanies any mention of protein homeostasis at family BBQ’s. Thankfully, our beach side home of Wollongong provides plenty of inspiration!

My scientific passion is understanding how each cell in our body achieves the world’s greatest balancing act - keeping all of its basic building blocks, proteins, in their correct three-dimensional conformation and therefore a functional state. Cells have an intricate network of ’lifeguards’, the proteostasis network, who monitor the proteins (or swimmers), keeping them folded and active or sending them to be degraded when they are no longer functional or needed. When there are disruptions to these lifeguards, the swimmers begin to drown (misfold) and can take others down with them (non-functional proteins accumulate) - at which point our cells begin to die. In the case of neurons, this cell death manifests as diseases like Alzheimer’s, ALS and Parkinson’s disease. It is therefore immensely important for us to understand why proteins begin to drown, how the lifeguards work and what contributes to their failure.

Much of my PhD work centered on one type of lifeguard - the small heat shock molecular chaperones. These lifeguards essentially patrol the beach, watching the swimmers, and spring into action when they detect a swimmer in trouble (a misfolded protein). Unfortunately they don’t have the ability to completely rescue a drowning swimmer (refold the protein), but they are quite good at bringing them back to the clubhouse and keeping them safe until help arrives (holding the protein in a folding-competent state). I focused my research on understanding how the small heat shock proteins help the swimmers (do they give them a life-ring? a pair of floaties? when do they hand them over to the experts?), and whether there was anything they could do once the drowning swimmers started to accumulate.

As a result of my PhD research, we now know that there are many ways the small heat shock proteins can interact with a particular type of swimmer (a-synuclein, whose misfolding and accumulation leads to Parkinson’s disease). Understanding these fundamental mechanisms is a crucial step in developing therapeutics to target the cellular lifeguards, to help treat or cure the diseases that result from their failure.

a year in review

Wed, 10 Jan 2018 10:50:36 +0000

This week kicks off 2018, and can I just say - about bloody time.

I know I’m not the only one - but 2017 was a bit of a roller coaster for me, both personally and professionally. I started a new job, in a new city, working in a new field. I made new friends, rented a new apartment, joined a new gym, and bought two new cars. My partner and I learnt new things about one another, and together we set a new personal best for flights between Melbourne and Sydney in a year. Between all of the new, a few old habits reared their ugly head - I worked consistently 10, 11, 12 hour days, weeknights and weekends. When I wasn’t at work, I was thinking about work. About how much I had to learn, and how out of depth I was. My old friend Impostor Syndrome came to visit, and set up camp on my new couch for a solid four to five months. Old health issues came back to bite me. It took me a really long time to feel at home in the lab again (settling into a new lab space after 4 solid years in your old one is hard, note to self), and I found it hard to balance my expectations with the reality of what was physically achievable in a single day. Lesson one of 2017 was balance, above all else. Balance is essential for mental and physical health, and without it you will drown.

Perhaps worst of all, I said yes. Consistently, for 9 months, I said yes to taking every meeting, trying every experiment, attending every outing… I was terrified of missing out on that most important opportunity. Six months into my new job, I was already juggling more than 10 ‘projects’ - each of which was substantial enough to occupy an honours student for a year - and had little idea which of them was actually paying my rent. Instead of giving myself a chance to settle in, maybe tackle a few key projects that would quickly generate data, I tried to chip away at everything and wound up floundering amongst a sea of failed experiments and next to no progress. I was burnt out, and looking for any way to slink off into the darkness and away from the academic career I had been working toward for the past decade. Lesson number two of 2017 was that it is ok, and in fact important, to say no. Sometimes. A handful of productive projects are better than a wealth of failing ones. It’s ok to be up front with your limitations - some people (the good ones) will respect you even more for it.

Despite all the heartache, I didn’t quit. Sometimes, hanging on for dear life is enough. I have a beautiful partner who reminded me everyday of why we were here. I have wonderful friends and family who boast proudly about this crazy scientist they know. These are the things that keep you going. Lesson number three of 2017 was keep these people close. They are your life blood.

Towards the end of the year, the waters started to smooth. I kicked my ImpSyn friend off the couch, made daily exercise a priority and devoted some time to personal goals. One of those was this (which I admit is still a work in progress). I also enrolled in an online course to pursue some extra-curricula computer programming skills. I finally engaged with Twitter (and oh what a wonderful, welcoming community I have found there). I worked to connect all my fabulous women friends in science as we go our separate ways for now (more on that later). Lesson number four of 2017 was don’t be afraid to know your goals, and to prioritise them. Nothing ventured, nothing gained. Even if it’s only small steps once a week or once a month, every little bit of effort will take you one step closer to your goal. And life is too short to keep these goals hidden out of fear.

The year came to a close in a wonderful corner of the New South Wales south coast. We beached, waterskiied, flew kites, ate tremendous icecream and slept. I had eight (yes, eight!) whole days without opening my computer, or even thinking about work. Those eight days were the happiest I spent in 2017, and after them I felt like I had opened the floodgates. In the back of my mind, I started to develop experiment ideas, fellowship projects and potential collaborative ventures. Suddenly, I couldn’t wait to get back to work to put things in motion. Lesson number five of 2017 is that in order to go fast, you must first go slow. A few people whom I deeply respect have mentioned this before, but it wasn’t until my summer holiday that I truly understood their meaning. This is my 2018 mantra.

These lessons, despite being painful to learn, have opened the door to an exhilarating 2018. I’m heading to three conferences over the next five weeks, which will mark my first national conference oral presentations. I’m attending a summer school, where I get to focus solely on developing my programming skills for six days straight. I am working on Fellowship applications which, if successful, will have me headed overseas in no time. My friends-in-STEM community continues to grow. For the first time in a while, I am excited about the upcoming few months. After the butt-kicking 2017 gave me, I finally feel like 2018 is the time to fight back.

Here’s to 2018. May it be full of science, love, laughter, growth and success for you all x

ideas on what helps and hinders symposium speakers

Mon, 27 Nov 2017 20:28:25 +0000

During the recent , a friend was scheduled to give a talk about her work. Sitting in the audience watching a parade of marvellous speakers is a special kind of torture, when you are convinced you could not possibly achieve a similar performance. I should know - until the very last year of my PhD, I was not a very talented communicator either. However, after a venture overseas and a stint in a different lab, I found my voice. I wouldn’t say I’m brilliant (far from it), but I have realised the importance of this aspect of science communication and worked hard at being able to at least stomach the idea.

My friend asked how I’d done it. How do you overcome the paralysing fear most people associate with public speaking? I didn’t really have an answer for her at the time - I encouraged her to be confident, which is of course the main ingredient. However, I have thought about it since then, and while watching the remaining conference talks I came across a few things that as an audience member I think can make or break a presentation.

1. Don’t repeat your talk name and title - people can read the program and your first slide (we are mostly smart cookies after all), and it is the job of a good session to chair (also presumably a smart cookie) to give those details when they introduce you. Instead, open by thanking the organisers for the opportunity to present some exciting new work, and a one line teaser to grab the audience - tell them why they should pay attention RIGHT NOW, and not wait until five minutes into your talk. If you don’t have them at the beginning, there will be no getting them back.

2. Oh, you’re skipping your introduction? Because EVERYONE ELSE has given this intro? At a conference specifically about your topic? NO WAY?! Think about your audience early on in the talk’s preparation stage and don’t be afraid to adjust on Day 1 of a three day event. If available, check out the program/other abstracts early, highlight talks with relevance to yours and gauge the level of any remaining introduction that you will need to give. Being able to refer to someone else’s intro not only shows you have engaged with the symposium but also gives you more time to go through the exciting bits (your results!)

3. Keep it simple, stupid. Most of the time you will have a very short window in which to convey your story, which will inevitably be the result of months and months of your blood, sweat and tears. Trying to cram too much into this time window makes your story confusing and hard to follow (10 tiny bar graphs on one slide, anyone?) and people will loose interest. Focus on a simple message, tell people what they need to understand that message, tell them what the message is, then reiterate why your message is important. Simple. As a bonus, people will chase down details with questions, avoiding the dreaded crickets-and-tumbleweeds at the end of a particularly confusing or dense talk.

4. Following on from this, constantly telling people you don’t have time to present this, that or the other (in an effort to keep the slides simple), sounds arrogant and selfish - figure out a story that you CAN tell in the allocated time and reiterate that you are happy to talk details during the breaks.

5. Fake it till you make it. This one has stood the test of time, and for good reason. So much of our perception of a good presenter is taken from their physical cues - and that stems entirely from confidence. If you are nervous beyond belief and terrified of doing something wrong, that will inevitably come through in your body language. If you own your talk and your work, that will come across instead. I think of this like you are the pilot of a plane - if you sound scared and uncertain, your passengers are going to be unsettled and anxious, leading to this cycle of negative reinforcement. If instead you get on the PA system, calmly detail the weather or flight plan (how would they really know how high you’re going to fly??) and make them believe you are in control of the situation, your passengers (the audience) will be calm and the atmosphere relaxed. Everyone will make it out alive and live happily ever after. Or so we hope.

Got any good tips that I’ve missed? Let me know your secret ingredient!

a few words on why I'm here

Sun, 26 Nov 2017 09:15:24 +0000

Truth be told, I don’t know that even I am sure why I am here. But if I am honest, I think the idea has been tumbling around, gathering dust, in the back of my brain for a while.

In 2013, I travelled to Cambridge, UK for 6 months as part of my postgraduate research. I had many people who asked for updates and photos of my travels, and the first ‘site’ I ever established began with that in mind. To this day, it has never progressed. I was always intimidated by putting my thoughts on ‘paper’ and the idea that I would spend time writing non-scientific pieces seemed ludicrous during my PhD. However, I am starting to understand the value of this process.

“Start writing, no matter what. The water does not flow until the faucet is turned on” - Louis L’Amour

So my goal is to write. To ramble, in fact! Many of the blogs I regularly read give similar things - a sense of reassurance that the way I feel and the experiences I have in the world of science are not unique, and I am not alone. My thoughts may not be that helpful, interesting or insightful, but it will be me. Conquering my fear. Maybe that is all I can hope for.If you’re reading this, thanks for jumping on board with me. I really appreciate your support and hope you find something of value to add to your scientific journey.

For-Everyone | DEZERAECOX

Terrific TDP-43 Talks in Trieste

Terrific TDP-43 Talks in Trieste

Toolbox Talk: Notion

Toolbox Talk: Notion

Need a notion about Notion?

A simple sneak peek

Ok… But what about Notion for science?

My Notion Nitty Gritty

Tips for getting started

Wrapping up

Year in review: 2020 Edition

Year in review: 2020 Edition

Wins

Losses

Lessons

Goals

Learning to code: it's as easy and as complex as that.

Learning to code: it’s as easy and as complex as that.

Final thoughts

Resources:

A year in review: 2019 edition

Wins

Losses

Lessons

Goals

Book Review: Spineless

The nitty-gritty details:

Overall thoughts:

Some of the best bits*:

Handy links:

Toolbox Talk: Storing data using HDF5 files

Data: the invisible bits and bytes of modern life.

What on earth is HDF5?

Pros and Cons of the HDF5 format

Sounds great.. But how do I use HDF5 files?

A few final thoughts.

Resources

EMBL Proteomics in Health and Disease Mechanisms 2019

Conference details:

There’s a first time for everything!

Overall scientific programme and conference feel

So conferences are just an excuse to travel?

Lessons learnt

Final thoughts

#LorneProteins2019 & #FASEB2019

Setting the scene.

What is tetraphenylethene maelimide, other than a tongue twister?!

But what about the giant protein soup our cells make, I hear you ask…

How does this help us understand disease mechanisms?

References and handy links

A year in review: 2018 edition

Wins

A snapshot of the high points

Losses

A snapier shot of the low points

Lessons

The bits I wish I knew at the start of 2018, but had to learn the hard way

Goals

Hopefully to help me meander with purpose through 2019

NoBell Prize 2018

Book review: The Effective Scientist

Toolbox talk: Atom, Jupyter and Hydrogen

The basics: Atom as a building block.

The best bits: Git(Hub), Integrated Development Environment and Real-time Collaboration functionality

Easy extensions: Size may not matter, but it’s all about the package(s)

Accessorising Atom: a Python perspective

Better than basics: integrating python virtual environments

Further Reading: Example Atom/Jupyter/Hydrogen/VirtualEnv Setup

Step 1: Checking your default Python install

Step 2: Install virtualenv, virtualenvwrapper

Step 3: Configure virtualenvwrapper

Step 4: Create virtual environment

Step 5: List, activate and deactive virtual environments

Step 6: Install relevant packages for your new environment

Step 7: Install new ipython, and configure a kernel from within the environment

Step 8: Install Atom packages

Step 9: Using the virtualenvwrapper package in Atom

Conclusions

Quick Recap: PyLadies Melbourne Event

**Some of the best bits*:**