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  The Evolution of Stochastic Regular Motifs for Protein Sequences (2002) [6 citations — 1 self]

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by Brian J. Ross
New Generation Computing
http://www.cosc.brocku.ca/~bross/research/sredna_ngc.pdf
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Abstract:

Abstract Stochastic regular motifs are evolved for protein sequences using genetic programming. The motif language, SRE-DNA, is a stochastic regular expression language suitable for denoting biosequences. Three restricted versions of SRE-DNA are used as target languages for evolved motifs. The genetic programming experiments are implemented in DCTG-GP, which is a genetic programming system that uses logic–based attribute grammars to define the target language for evolved programs. Earlier preliminary work tested SRE-DNA’s viablility as a representation language for aligned protein sequences. This work establishes that SRE-DNA is also suitable for evolving motifs for unaligned sets of sequences. ∗1

Citations

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