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Extended Compact Genetic Algorithms and Learning Classifier Systems for Dimensionality Reduction: a Protein Alphabet Reduction Study Case

by Professor of Computing Science and Synthetic Biology at Newcastle University on Jun 30, 2009

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In this talk we demonstrate an ECGA and LCS pipeline for reducing protein alphabets from the standard 20 to 5 or less symbols without significant loss of information. The pipeline tailors the ...

In this talk we demonstrate an ECGA and LCS pipeline for reducing protein alphabets from the standard 20 to 5 or less symbols without significant loss of information. The pipeline tailors the reduction to different problems thus resulting on different optimal minimal alphabets.

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Extended Compact Genetic Algorithms and Learning Classifier Systems for Dimensionality Reduction: a Protein Alphabet Reduction Study Case Extended Compact Genetic Algorithms and Learning Classifier Systems for Dimensionality Reduction: a Protein Alphabet Reduction Study Case Presentation Transcript