Supportive Courses for Bioinformatics?

Per Christian Henden asks: "I`m aiming for a masters degree in bioinformatics, and I`m uncertain which courses would be good to follow (and my counselor doesn't know, either). There are of course some courses that 'belong' to this degree, and I`ll take those, but I get to choose a number of additional courses. I want to ask people working in bioinformatics 'What (CS) subjects are important or especially useful in bioinformatics?' I`m planning on choosing 'Large Datasets', 'Parallel Programming', 'Image Classification', and 'Subsymbolic AI', because I think those are important, but I`m really not sure what is useful or not in real life bioinformatics." Other Ask Slashdot articles, which have touched on bioinformatics, have dealt with magazines, books and graduate schools.

Comments

You Need Biology

[JunkDNA]

I work for a huge Bioinformatics department at a major pharmaceutical company. One thing you need to understand is that the lion's share of Bioinformatics would probably be considered "run of the mill" stuff as far as the rest of computer science is concerned. The biggest problem in Bioinformatics is that our IT people lack sufficient understanding of the underlying biology. If I had to pick an ideal candidate for a position with us, I would look for the following (in order of importance):

Biology background that includes some of the following undergraduate courses: molecular biology, genetics, evolutionary biology, biochemistry/biophysics, virology, & microbiology

Computer background that includes many of the following: Perl, Java, relational databases, XML, Visual Basic (lots of stupid stuff uses it) & general UNIX skills

Preferably some kind of lab experience

Any background in statistics (the more the better)

What we really need are people capable of integrating large amounts of data (DNA sequences, protein structure info, gene expression results, biochemical pathways, clinical data, etc...). This stuff all needs to tie together somehow. While this doesn't require massive programming heroics, it does require an attention to the underlying science or else the wrong assumptions can be made and a total disaster created.

Now, that's not to say that people with experience in areas such as artificial intelligence, image analysis, or natural language processing wouldn't be assets, but to be honest, we're just not at that point yet. Some actual Bioinformatics companies and organizations (TIGR, Celera, Affymetrix, Rosetta, etc...) may (and probably do) have a need for these specialized skills more than us. But do yourself a favor and take as much biology as possible. It's invaluable to my "office karma score" to be able to discuss the latest on Slashdot with our programmers, and two minutes later talk about an article from Nature with our biologists.