Re^2: Other Bioinformatics Monks Out There?

in reply to Re: Other Bioinformatics Monks Out There?
in thread Other Bioinformatics Monks Out There?

And what is your background? Are you a neurobiologist by training who happend to play a lot with programming, and found that he could put that to use in his work? Or are you a programmer by trade who realised that some of the more interesting problems - with real-life applications - are to be found in biology?

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Re^3: Other Bioinformatics Monks Out There? by kvale (Monsignor) on Aug 04, 2004 at 20:44 UTC
I am a theoretical physicist who decided there is a lot of potential for quantitative techniques to be applied to neurobiological problems. Theoretical physics is often portrayed as one of the more difficult, deep sciences. While it is true that physicists often use esoteric mathematics, physicists pick their problems and theories to be analytically tractable, or at least analytically approximable. Biology is none of this. Biological systems are nonlinear, nonequilibrium, and nonstationary. Dealing with such systems is at the forefront of physical techniques and beyond. That is where the fun is. I've had a love of programming and hacking ever since I was a kid, so it is natural for me to attack these problems computationally. Perl came to the fore mostly because I can program in perl faster, with fewer bugs, than any other language I have learned before or since. In addition to PDL mentioned before, perl is used for keeping track of experimental databases, data munging, GUI design through perl /Tk, and glue that holds the whole data analysis protocol together. -Mark	[reply]

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Re^3: Other Bioinformatics Monks Out There?
by kvale (Monsignor) on Aug 04, 2004 at 20:44 UTC

Theoretical physics is often portrayed as one of the more difficult, deep sciences. While it is true that physicists often use esoteric mathematics, physicists pick their problems and theories to be analytically tractable, or at least analytically approximable. Biology is none of this. Biological systems are nonlinear, nonequilibrium, and nonstationary. Dealing with such systems is at the forefront of physical techniques and beyond. That is where the fun is.

I've had a love of programming and hacking ever since I was a kid, so it is natural for me to attack these problems computationally. Perl came to the fore mostly because I can program in perl faster, with fewer bugs, than any other language I have learned before or since. In addition to PDL mentioned before, perl is used for keeping track of experimental databases, data munging, GUI design through perl /Tk, and glue that holds the whole data analysis protocol together.

-Mark

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