Bioinformatics Zen

Computational biology moves fast in comparison with traditional biology. All it takes is a few lines of code to produce results. Contrast this with the wet lab, where every step usually requires a full working day, or more. Difficulties with direction, often arise from having too much data, rather than not enough.

As such, in bioinformatics, it’s important to keep focused on what you are trying to achieve. Do you need to add the extra search feature to your tool? What does it add? Can the question be answered with what you’ve built already? I threw away 10,000 words from my masters thesis because I lost direction. Here’s three practical ideas that I use to keep focused.

Talk about your work
Talk to someone about what you’re up to. Go for a coffee and have a chat about it. Speaking about what you’re working on gives you a fresh perspective. You have to vocalise all the jumbled ideas in your head into a coherent trail of thought. This will immediately tell you where the weak points are, even before the listener has a chance to respond. Whoever you’re talking to will ask questions, point out obvious flaws, and tell which bits are exciting. All which will help you focus on which areas you should be working on.

Write about your work
Keep a log describing what you’ve been doing. Just a few sentences each day. Writing down what you’ve been doing, like speaking out loud, makes you think in a different perspective. If you have a supervisor, write small reports on what you’ve done. This can be useful to get feedback if they’re usually too busy to see you.

Review your work
Every so often I look at my log and ideas book. What direction is my work taking me? What’s changed since last week? Have I taken a different route to what I originally intended? Am I still heading in the right direction? Occasionally I realise I’ve gotten side tracked into something which is not relevant. Usually then it’s a good time to go back and re-evaluate what my long term goals are. For example what is the title of the paper I’m going to write.

Scientists have to be left brained, rational and analytical. But at the same time very right brained, inventive and holistic. We produce ideas, and often make a creative leaps to connect previous work and new concepts. Your ideas are part of you as a scientist.

If like me, you’re a touch obsessed with your work, you probably think about it everywhere. Maybe you talk abut it with your partner over dinner? How about standing in the shower running things through your head? But how often have you come up with an idea that you’ve quickly forgotten?

For me, writing down every idea I have has been one of my most worthwhile habits. I find that writing down ideas is an activity that gets better with practice. By giving my creative side the attention it deserves, I find that I become more confident in making that important leap - good ideas come more frequently.

Have a hard copy of your ideas is also very handy when you hit a dead end, you’ve got plenty of material for new inspiration.

Here’s three different example systems I’ve used for storing ideas. All have a huge following as a method for keeping organised. I’ve included a link to more information on each.

Moleskine
A little black book with a folder at the back, and a strap to keep it closed. Hard wearing and a pleasure to write in. Looks pretty cool too. It was in my moleskine that I sketched out my ideas for Bioinformatics Zen. Just don’t lose it though.

Hipster pda
A set of cards held together by a bulldog clip. This has a huge following in the GTD community. Once you’ve written an idea you can pull the card out, leave it on your desk, and process it when you’ve got more time. Well worth giving a try - mine cost 30p to make.

Index cards
Slightly more tricky to carry a box of index cards around. More useful in the office. I’ve got a wall next to my desk covered with index cards, each with a single idea on. Handy when you’re writing documents and need to refer to something you thought of a while ago.

A great post at creating passionate users. The point - user manuals are REALLY important.

Bottom line: never underestimate the value of providing fabulous training materials in getting–and keeping–users motivated to get better. And the better they are, the more likely they are to appreciate (and buy) your higher-end versions, evangelize, buy and create accessories, etc.

I really like head first books. Based on getting you to learn the way your brain wants to, I think their method is fantastic. But could these principles can be applied to science too?.

Reading scientific literature takes a lot of effort. Sitting still and focusing on what the author wants you to understand, requires energy and concentration. What if the principles of the head-first learning series were applied? The stuff in science books and papers is, after all, some of the most difficult material you’re likely to read. We would benefit if this material was communicated in a way that would help us learn best.

“That’s easy for you to say, but how do we do it?” I hear you say. Well, I put my money where my mouth is. I created a short guide to making graphs in R, using what I hope is an effective method of communicating a difficult topic.

You can download the pdf of this guide here.

You love making programs that reveal yourself as a programming god. You produce results that demonstrate you are, quite obviously, the greatest scientist of our generation. You show these to everyone in your office/corridor/family, they all appreciate your magnificence. After a few talks at conferences comes the bit you’ve been avoiding - writing everything up.

I think I’m fair in saying that you went into bioinformatics for something other than writing reports and papers. At some point though, you have to.

Set a daily goal
When I have to write, I set a goal of 500 words a day. Even if they are complete nonsense, which they usually are. Writing, like everything else, gets better with practice. My writing usually becomes more coherent, the more I do. Once you’ve got everything written, even if it’s rubbish, you’ll feel much better. You can start editing for clarity later.

Throw away as much as possible
You’ve written huge amounts of text, so why bin all the effort? Because you’re writing for other people. Everyone one has to expend energy to read your work. Think about how dull it is for you reading badly written text. It’s a boring activity that you have to force yourself to do. Now what if the document had instead been composed with the reader in mind? The point is put across in clear and simple terms. Every paragraph, sentence, word is there because it has to be.

Learn how to write well
Writing, like presenting, is a skill that doesn’t receive as much attention as it should. Particularly in science where, quite rightly, the emphasis is scientific method and ability. But once you have your results, you need to communicate them. I’ve found that becoming better at writing makes you more confident, making writing more enjoyable and a less arduous task.
To this end, I recommend Strunk and White, “The elements of style”. Fortunately, this book is also available online.
Also check out this page for a practical introduction to writing.

Finally, if you’re taking one thing away from this post, please take this.

Vigorous writing is concise. A sentence should contain no unnecessary words, a paragraph no unnecessary sentences, for the same reason that a drawing should have no unnecessary lines and a machine no unnecessary parts. This requires not that the writer make all his sentences short, or that he avoid all detail and treat his subjects only in outline, but that every word tell.
William Strunk Jr., Elements of Style

Forty two words were thrown away in revising this post. Coincidence?