Personally my background is in CS and genetics -- within CS my
concentration was in machine learning and algorithms. I've been working
in bioinformatics for 5 or 6 years now and I'd have to say as the data
sets become larger and larger they lend themselves more and more to a
machine learning AI approach to analysis.
Initially algorithms based on searching large spaces -- GAs, beam searches
etc, but AI classification schemes are used quite a bit in
specific analysis. I did a some work using KBANN (knowledge based
artificial neural nets) for exon prediction, markov models, baysian
classification networks etc for many different sub problems in biology and
bioinformatics. Text classification schemes are used somewhat naively in
trying to do automatic annotation also -- but I see a lot of room for
improvement there.
If you are interested or would like to know more I can talk or try to
point you in some relevant directions.
-lee
On Sun, 12 Aug 2001, Nathan Torkington bestowed the following wisdom:
Simon Cozens writes:
there were AI people doing work in the field. If the one response
I've received is anything to go by, I guess not :-)
Nat
I can put you in touch with a couple of bioinformatics/Perl people, but
I don't know how much or if that would help.
Thanks, but I already know a few. I was more interested in whetherI don't know how much or if that would help.
there were AI people doing work in the field. If the one response
I've received is anything to go by, I guess not :-)
Nat
