Getting Experience In Bioinformatics
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8.8 years ago
user5189 ▴ 20

What's the best way for people with novice programming skills to get experience in bioinformatics or cheminformatics? Are there any open source projects to volunteer for? Would it be worth it to approach a professor working in bioinformatics and offer to help him/her?

About me: I'm a graduate biochemistry student about to graduate. I'm a self-taught, novice programmer, eagerly learning more all the time; but I want a real world problem to work on. If at all possible, I'd like to work on something collaborative (so I could have build relationships supporting a "professional reference"), and something real; beyond just exercises in a textbook.

bioinformatics chemoinformatics • 5.0k views
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+1 Michael's comment - rosalind (which this post describes) looks like a great way of developing a host of particularly bioinformatics-relevant skills, while strengthening in general many core programming skills, which I think is a great thing to develop if you are self-taught

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I would suggest you to learn Python and its various libraries for bioinformatics like Biopython, PyCogent etc. Additionally some shell scripting and unix tools like sed, awk etc will be very useful.

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your idea of getting involved in volunteering for projects I also find a good one - that way you can be working as part of a community, in a context where you'll hopefully get more feedback than if you just plug away on your own. Perhaps something where there could be some relatively "simple" things that need fixing/working on e.g. bioperl, would be a good place to go for this.

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Also, I recommend you get involved in any local meetings of bioinformaticians. Last year I, and a bunch of others, started running meetings for our local-area bioinformaticians, and for us at least (the organisers), but I'm also sure many other participants too, this has provided improved/more relationships of the kind you describe (and have been fun too). I'll shamelessly link to the kind of stuff we've been doing here: http://hub-hub.de as I've ended up being surprisingly pleased with what we've done, maybe interesting for others to see; if nothing like this exists where you're working, maybe you'd like to try and set something like this up yourself?

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8.8 years ago
Josh Herr 5.7k

I'm going to chime in here, but all the previous comments to your question are excellent suggestions on where to start. There's typically a question a week in this forum like this so there's lots of places for suggestions. The "Tutorials" tab here is a great place to start, and Google is your friend.

You're a biochemistry graduate student who already has some programming experience and is interested in something beyond workbook exercises -- I think you probably possess all the questions in your own research and research interests to really delve into bioinformatics and develop your skills. I would suggest taking an area of your research (I don't know what this is), but then focus on how you can begin to develop your bioinformatics skills by focusing on your own research questions, perhaps in new ways, perhaps not.

I've found that I have plenty of text manipulations (protein or nucleotide sequences) where I have needed to develop my Python, Perl, and shell skills; trying to determine significance and graphing of data from microarrays and RT-PCR taught me to use R; trying to understand homology of proteins (years ago) taught me to really focus on phylogenetics and my first taste of the command line. I still am a novice, but I try to learn a little bit every day. Even if you're strictly a wet lab person now, surely you have some data which you can either investigate using bioinformatic tools or could accent with plenty of publicly available genomics data related to what you study. Asking questions about your data and looking at how you can strengthen your own data using a new tool will help.

I would (1) start with a question related to your research (old or new to you), and (2) try to figure out how to begin to develop a strategy to answer this question (i.e. develop your algorithm) and then (3) figure out which bioinformatic tools your need to learn to answer the question and dive right in. We're here to help you with the "diving in" part.

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