Women in Technology

Hear us Roar



Article:
  Introduction to Bioinformatics
Subject:   More than just blind data munging
Date:   2004-06-14 05:47:18
From:   bioinfotools
I like to gently broaden your remark:


Third is the reality that bioinformatics is not a theoretical science; it is driven by the data, which in turn is driven by the needs of biology. Relatively few researchers have the luxury to develop algorithms and theories in the traditional academic sense. Most people are fully consumed in the day-to-day management and analysis of data.


My perspective might be idealistic, but the reasoning behind it might be worth thinking about.


The view you present is certainly present in many bioinformatics support groups, but I have I have mixed feelings about it. I worry that a lot of people don't think enough about the fact that the methods are (done properly) encapsulations of models of biological theory. Unless you understand that underlying theory well enough, you're going to use the tools in a sloppy way.


The reason I worry, is this that much the bulk processing is vulnerable to a bioinformatic variant of the old garbage in - garbage out rule.


Likewise, if you are going to develop new analytical methods, you had better have a deep understanding the biological systems involved.


There is plenty of need for "straight" IT - sys. admin., GUI designers, web services, databasing, etc. There is a wide range of skills used in the bigger teams ranging from the computational biologist who is thoroughly versed in the subtle aspects of the field through to the local "Unix geek" who can run rings around anyone in the place in the command line but who knows damn-all biology. The high-throughput stuff is needed and probably the bulk of these teams aren't at the computational biology end of the spectrum, but someone along the way needs to take responsibility for the approach used. People coming to the field should think about where they belong on that pipeline.


Data management does take up a large part of most research projects (of any kind), but at the heart of it will be some analytical processes.


For those wishing to get into the algorithmic side of things, there certainly is scope for new developers from straight IT backgrounds -- but under the guidance of someone experienced to ensure that what they are doing is meaningful. I'd second another poster's advice to work under someone who has experience in the field first. There are plenty of studentship, internship, etc., opportunities out there.


Hmm, this got rather long. Must have lit my wick :-) I Hope this isn't wasted bandwidth.