About: Cleavage site prediction is an important issue in molecular biology. We present a new method that generates prediction rules for SARS-CoV protease cleavage sites. Our method includes rule extraction from a trained neural network and then enhancing the extracted rules by genetic evolution to improve its quality. Experimental results show that the method could generate new rules for cleavage site prediction, which are more general and accurate than consensus patterns.   Goto Sponge  NotDistinct  Permalink

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  • Cleavage site prediction is an important issue in molecular biology. We present a new method that generates prediction rules for SARS-CoV protease cleavage sites. Our method includes rule extraction from a trained neural network and then enhancing the extracted rules by genetic evolution to improve its quality. Experimental results show that the method could generate new rules for cleavage site prediction, which are more general and accurate than consensus patterns.
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  • Artificial intelligence
  • Chemical bonding
  • Internalism and externalism
  • Econometrics
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