Bioinformatics FAQ (Frequently Asked Questions) - Newbie getting started

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Courses biologists might consider taking:

UNIX

Of all the computing courses available it is most important that you have a proper introduction to the UNIX operating system(s). Most current bioinformatics software (especially the free stuff) runs on "open" platforms like Linux and the Web. The UNIX philosophy is elegant, powerful, and frustrating. Master it and you will save a lot of time.

Mathematics

Learn some maths. Basic statistics, logic/set theory and a little calculus would be my recommendation. Many practising biologists have little or no grasp of elementary concepts like statistical significance, permutations and combinations and the principles of good experimental design. Logic will come in handy at the very least if you want to query databases in an intelligent way.

Programming

If you're interested in development, learn a real programming language: Pascal, C(++), Java or Fortran.

Perl and HTML are the stuff that holds the Web together. A grasp of these is essential for a lot of the Web/database work being done by many bioinformaticians at the moment.

Good old BASIC can be very useful as an introduction to programming or as a tool in its own right, but none of these latter languages is built to crunch numbers and tackle real world biological problems---which isn't to say people don't try...

How can I get involved?---I am a computational/quantitative scientist

One thing that I will emphasise repeatedly in this section is the simple value of doing some "proper" biological laboratory science. I have sat through many talks during which a bioinformatics "scientist" describes in great detail how his---it's usually "his"---application of a trendy mathematical tool offers a supposed insight into a (sometimes supposed) biological problem. Nine times out of ten I know that this method will never be so much as sneezed on by a practising biologist.

Quantitative scientists sometimes talk about their interest in studying some aspect of "God's mind". Biologists, in contrast, are interested in "Mother Nature". You might meditate on God in the hope of some revelation, but to understand Nature you have to meet her in the flesh. You are as likely to be useful to biologists working in isolation at the keyboard as you are to conceive with your clothes on. Desk-bound bioinformaticians have written code that has turned out to be popular with biologists, but almost always because they have collaborated with biologists.

Courses quantitative scientists might consider taking:

Molecular biology

"MoBi" was the bioinformatics of its day; desperately fashionable, the province of new, higher-paid practitioners and considered with slight suspicion by more traditional biologists. It was once a great achievement to sequence a modest stretch of DNA, now it's a job for robots. Today the technology of molecular biology is very well established. Scientists can buy kits to perform the sort of genetic manipulations that would make your parents' jaws drop. Some of the kits are so simple your small children could use them (with a modest amount of training and supervision).

Despite the profusion of commercial kits, there is still a requirement for real skill in molecular biology and the general level of scientific understanding required to be a good biological scientist---rather than just completing a practical class---doesn't come easy. Living matter, the stuff you have to work with is unpredictable and responds slowly---except when it's dying. Even supposedly fast-growing bacteria can take a long time to yield up their secrets.

Now, fashions in biomedical research are shifting from molecular biology back to cell biology and protein biochemistry, but it's well worth offering yourself up as a volunteer for some vacation work in a molecular biology lab. The term is now more often used to refer to the technological tools provided by MoBi to biology in general, rather than to fundamental research in the field itself. Those tools are common to a vast array of different kinds of research, from archaeology to zoology.

(Continued on next part...)

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