Bioinformatics in The Economist

Erich Schwarz writes "Bioinformatics has gone from being an esoteric sub-field to being a business. The Economist gives a useful overview, while warning 'Bioinformatics is not for the faint of heart...'"

Comments

Bioinformatics runs on Open Source

[dan dan the dna man]

So don't sit there saying its hard to get into :)

Run, don't walk to bioinformatics.org and contribute!

The first O'Reilly bioinformatics conference rocked. Shame I wont make the next one in San Diego - I get to go to Adelaide for the ISMB in June instead :)

Re:Bioinformatics runs on Open Source

[glwtta]

Or go straight to bioperl.org, one of the absolute key projects for bioinformatics.

In case you are wondering, there is a biopython, biojava, biocorba, bioxml, biruby, etc. but perl is really where 90% of bioinformatics is done (simply because, in the end, all it is is text processing)

Re:What I'd major in

[coloth]

this combination can be hard to come by

I guess there'll be a few with outright credentials, some more who are smart enough to wing it while they learn what they're missing, and a lot of people who contribute as part of a team.

If you haven't read Ship of Gold by Gary Kinder, about Tommy Thompson's life and eventual recovery of $1 billion in gold from the deep sea, I strongly recommend it, especially to any scientific or engineering-oriented person. Tommy's story is a case study in how to break new ground, think creatively, and form networks of expertise. It convinced me that credendials, and even past experience, may not be the best indicators of future success.

My $.02 on biological sciences

[t0rnt0pieces]

I graduated from Rutgers U. (decent NJ state school) in May 2000 with a bachelor's in biology. Back when I decided to major in bio, I really enjoyed studying the field, and (high school) teachers were telling me that molecular biology was the fastest growing job sector. So by the time senior year came around I began looking for a "real" job. I checked all the papers, company websites, monster, etc. and realized that there really are NO good jobs out there for biologists. There are a few bioinformatics jobs, but guess what, you need a CS degree for them, not biology. I ended up getting a lousy job as a lab technician paying around $14 an hour (which took several months to find, btw, and this was when the economy was booming), and I'm extremely unhappy. I've completely lost any love I had for this field. Say what you want about money not being the most important thing, but when you can't afford to do anything you want, your life gets miserable very fast, I don't care how great your job is. Biology jobs typically have zero mobility and are extremely underpaid. You think there's a flood of people graduating from CS? Biology is far worse. My CS classes have about 20-30 people in them. My bio classes had hundreds.

Just recently I decided to go back to Rutgers for a second bachelor's in computer science. Not only are the job prospects better and higher-paying (even considering the dot-com collapse), I've always enjoyed working with computers and my grades are actually far better (although I was never a bad student). I'm actually having fun in my CS classes, I never had fun in bio. The classes were more like a chore. Another horrible thing about biology is that you really don't learn anything practical in college, you just memorize facts. At least with computer science you learn many useful tools to make you a competant programmer, which is actually a marketable skill. Nothing about biology is marketable. I highly discourage anyone from majoring in Bio unless they seriously, seriously love it and intend to get a PhD and devote their lives to research without regards to trivial things like money and job prospects.

Re:Bioinformatics, Genomics, Proteomics

[spiro_killglance]

I don't think protein protien interaction is
trivial either. Lets assume that both proteins say the same shape. Take one protein
rotate it and move it around the other protein
in all possible positions and orientations the
relavent group action is R(3) tensor O(3), (the group transitions of one body in 3d, times the
group of rotations in 3d:
six dimensions. proteins are big molecules,
for each of the possible orientations and positions you need to calculate the electrical and
pauli forces between each atom on the surfaces of
one protein with those on the the surface of the
other protein to see if the there can be any chemical interaction between the two. This is a
heavy ammount of computation. But its worse than
that one protein can change the shape of another
one making the calculations even more complex.

Proteomics needs the folding problem solved.
Protein Protein interaction solved.
The inverse folding problem solved (for drug/DNA design).
Then DNA-protein interaction, and the interactions
with macro sugar molecules. Once you've done all
that and have it tabulated in vest lookup tables
for common problems
and with computation on demand for rarer problems, then you can simulate a single cell.

Best sources of bioinfo ... for the curious ...

[Anonymous Coward]

http://www.ncbi.nlm.nih.gov/

and

http://genome.ucsc.edu/

Re:Bioinformatics, Genomics, Proteomics

[reverseengineer]

You make an excellent point, especially since it has been discovered that in the case of many of the cell's chemical pathways, one enzyme pretty much just hands off the substrate to the next enzyme in the chain, as opposed to letting it float around in the cytosol and find the next enzyme. So yes, protein-protein interactions are going to be a very important consideration for proteomics researchers. Unfortunately, we do have to walk before we can run. The current state of things is such that we have trouble figuring out how a simple oligopeptide will fold. We must figure that out, then more complicated peptides, then multi-subunit proteins like hemoglobin or rubisco, then we can hit up the protein-protein interactions. I'd imagine this sort of computation is going to require massively parallel computing on a scale that puts today's state of the art to shame, and probably some new ideas in applying pertubation theory. All that figures to keep computational chemists nicely employed for a long time to come.