Wednesday, September 07, 2005


GAs used in protein structure problem

Researchers at the University of Southhampton report success using genetic algorithms to evolve hidden Markov models for the prediction of secondary structure in proteins.
New results are presented for the prediction of secondary structure information for protein sequences using Hidden Markov Models (HMMs) evolved using a Genetic Algorithm (GA). We achieved a Q3 measure of 75% using one of the most stringent data set ever used for protein secondary structure prediction. Our results beat the best hand-designed HMM currently available and are comparable to the best known techniques for this problem.
An abstract of the work is available here.

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