ISMB 2008: "Career Paths in Bioinformatics and Computational Biology"

A panel discussion about "Career Paths in Bioinformatics and Computational Biology" was part of Friday's Student Council Symposium during ISMB. The four panelists were from academia: Philip E. Bourne (group leader at University of California San Diego), Alfonso Valencia (group leader at the Spanish National Research Council), Jong Bhak (director of the Korean BioInformation Center) and Richard Wintle (Assistant Director at The Centre for Applied Genomics). (Only RW had spent a longer time [6 years] in the industry at start-up companies.)

[All quotes are paraphrases based on the notes I took.]

Perhaps unsurprisingly, they couldn't offer real comforting answers to the questions of young researchers: "Isn't there a high chance that at the age of 40 you'll be highly trained and specialized, but without a job?" – "There's no job security in academia anyway; I'm not sure if academia is more competitive than industry" (AV). "After the initial boom in bioinformatics positions, will the fraction of grad students who become PIs approach biology with 5 to 10%?" – "Biology will morph into bioinformatics, so there will be more jobs." (JB)

However, I could take away some positive advice. In short: follow your heart, be passionate about something, don't do what everybody else is doing, start you own sub-field if you have to. From my perspective, this is both reasonable and encouraging. As I enter the last phase of being a PhD student, I begin to wonder how I can combine working in science and caring for my family. I guess I hope by staying motivated and by being effective in what I do I can have a chance to grow in my career and by there for my family. (I think this is a great advantage of computational biology: You can't make gels run faster, so to say, but you can be effective in programming and analyzing data.)

Another good insight was that a lot of basic, technological advances will come from industry in the future. Dr. Bhak cited the example of CPU development: The huge increases in processing power we see today is being implemented at Intel and AMD (although I cannot judge how much they rely on basic research by academia). My addition to this might be that part of bioinformatics will become more of an engineering discipline. So, for people interested in this, there will be a big job market in the future.

Similarly, the panelists expected that every biology lab will have embedded computational biologists in the future. I agree, but I think these will be mostly post-doc (i.e. non-permanent) positions.


Some of the questions and answers in more detail:

What will be the big opportunities in the next five years? The current generation of students will lead the bioinformatics industry, like the previous generation is currently leading in academia (JB). There will be many more embedded bioinformaticians (see above, AV). Hybrid skills (wet-lab and computational biology) will become more important (RW). The greatest opportunities are cross-disciplinary approaches that tackle as much complexity as possible (PB).

To stay motivated, and find out what you want to do: Always follow your heart in career decisions; create your own sub-division if you have to (PB). Don't do something just because it's trendy; what you like to do might change over time (at one point, industry might be appealing, later academia) (RW).

To find your spot in academia: Find influential people (RW). Diversify: try to do something that not everyone else is doing (AV).

Micro-blogging ISMB

As Pablo announced, several people including me are micro-blogging about ISMB on FriendFeed and to a lesser extent on Twitter.

Invoking TextMate from a remote machine

I edit all my script files via TextMate, but they live on remote drives (mounted via sshfs). I'm always logged in to the remote machines to run scripts etc. Usually I'll open remote files via Quicksilver, but when I create a new file this isn't an option yet and so it's tedious. Anyway, I've cooked up a quick script (with some help) to open TextMate from a remote machine.

Try it, YMMV:

#!/bin/bash

cd $(dirname $1)

PWD=`/bin/pwd`

BASENAME=$(basename $1)

ssh pasadena "osascript -e \
'tell app \"Terminal\" to do \
shell script \"/usr/local/bin/mate /Volumes/emil$PWD/$BASENAME\"'" >& /dev/null &

pasadena = name of my Mac OS X machine
/Volumes/emil = sshfs mount point

Update: I removed the "-w" option (I didn't want TextMate to wait for the file to be closed) and redirected all the garbage to /dev/null.

Update 2: Support arbitrary (i.e. also absolute) paths.

Update 3: this is broken on Snow Leopard :(

Update 4: Here's a workaround, although it's a bit ugly as you need to invoke sudo.

Unison is great for syncing files

I've already tagged Unison, but I find it so very useful that I just have to write this short blog post to praise it. If you work on two computers and want to keep a set of files in sync, you should try Unison. It's open-source, cross-platform, and the newest version works great on Mac OS X (fink's version was broken when I tried it).

In contrast to other syncing or backup programs, Unison is bidirectional. For example, I just edited some slides for a talk I'm giving tomorrow on my laptop, while I made some changes in the report on my main computer. Then I ran Unison, and it sent the files in the appropriate direction.

Minor gripe: I've tried to sync a huge folder with it and it failed (20 GB / 8600 files+folders), but it works fine and is fast for my normal syncing (350 MB / 1200 files+folders). However, in the first case I really wanted to make a backup, so I just used SuperDuper for this one folder.

Using Makefiles for jobs that run on a cluster

Makefiles are great. While you work on a project, they make it convenient to run the necessary scripts. When you come back to the project half a year later, you don't have to dig in your brain how the scripts fit together—it's all there. (More on make, and related advice.)

However, often in bioinformatics computational tasks are too big for a single CPU, so jobs are submitted to a cluster. Then, the Makefile doesn't help you much: It can't detect that jobs are running on the cluster. There is qmake, but it only works if all your parallel jobs are specified in the Makefile. I usually write my parallel scripts in a way that they can submit as many instances as necessary of themselves to the cluster via qsub.

Therefore, I went ahead and wrote a small Python wrapper script that runs the job submission script and sniffs the job ids from the output of qsub. It then waits and monitors these jobs until they are all done. Then, the execution of the Makefile can continue.

Here's an example of how to invoke the wrapper script from the Makefile:

pubchem_compound_inchi.tsv.gz:
   ~/src/misc/qwrap.py ${SRC_DIR}/inchikeys.py
   cat ../inchikey/* | gzip > pubchem_compound_inchi.tsv.gz

You can download the code (released under a BSD License, adapted to SGE). I hope it's useful!

Addendum: Hunting around in the SGE documentation I found the "-sync" option, which, together with job arrays, probably provides the same functionality but also checks the exit status of the jobs.

InChIKeys for PubChem

An InChIKey is a sort of checksum for chemical structures. It consists of two parts: The first captures the scaffold of the compound, the second is computed based on the stereochemistry, proton position etc. This makes the InChIKey ideal for STITCH, because we want to merge tautomers and stereoisomers.

PubChem doesn't provide an InChiKey yet in the SDF files that you can download. However, you can quickly generate a tab-delimited file with the help of the InChI toolkit (which you have to download and compile):

zcat SDF/Compound_00000001_00025000.sdf.gz | \
./cInChI-1 -STDIO -key -AuxNone -SDF:PUBCHEM_COMPOUND_CID | \
sed 's/Structure.*=//' | sed ':a; $\!N;s/\nInChI/\tInChI/;ta;P;D' > result

(The sed command is from a FAQ.)

Blogging for search engines

Related to my last post about the failings of Web 2.0 in biology, I want to ask the meta-question: Why do we blog? David Crotty proposes four reasons: Communication with other science bloggers, with non-specialists, with journalist and finally with search engine users. Unless you are a fairly well-known person, your regular audience will consist of your colleagues, collaborators and a random grad student or two. A journalist might only come by if you managed to get a press release about a Nature/Science/... paper out. But, Googlebot won't fail you and read all you posts!

Insightful blog posts won't stay without an audience. For one, the small circle of followers to your blog will spread the news if you write something worth sharing. Far more important are search engines. How do you survey a research area of interest? Most of us will query PubMed, but also do a Google search in the hope that some meaningful analysis is somewhere on a course website, in the text of a paper or maybe even in a blog.

Biologists use Google to query for their proteins of interest. STRING is a fairly successful database, and lots of people google for it by name. However, almost one quarter of all visitors from Google have actually searched for a protein name (random example) and found STRING. If you follow Lars J. Jensen's lead and publish your research observations and dead ends online, someone might serendipitously find them and use them for their own research. This will be the next steps towards open science (with open data, open notebooks—which we might never reach): "Publishing" small findings, data and back stories about papers on your blog, enabling others to gain insight.