Predicting enzyme class from protein structure using Bayesian classification.

Luiz C Borro; Stanley R M Oliveira; Michel E B Yamagishi; Adaulto L Mancini; José G Jardine; Ivan Mazoni; Edgard H dos Santos; Roberto H Higa; Paula R Kuser; Goran Neshich

PubMed · 16755510

Predicting enzyme class from protein structure using Bayesian classification.

Luiz C Borro·Stanley R M Oliveira·Michel E B Yamagishi·Adaulto L Mancini·José G Jardine·Ivan Mazoni·Edgard H dos Santos·Roberto H Higa·Paula R Kuser·Goran Neshich

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Abstract

Predicting enzyme class from protein structure parameters is a challenging problem in protein analysis. We developed a method to predict enzyme class that combines the strengths of statistical and data-mining methods. This method has a strong mathematical foundation and is simple to implement, achieving an accuracy of 45%. A comparison with the methods found in the literature designed to predict enzyme class showed that our method outperforms the existing methods.

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Algorithms Bayes Theorem Enzymes Humans Protein Conformation Sequence Alignment Journal Article Research Support, Non-U.S. Gov't

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Luiz C Borro, Stanley R M Oliveira, Michel E B Yamagishi, Adaulto L Mancini, José G Jardine, Ivan Mazoni, Edgard H dos Santos, Roberto H Higa, Paula R Kuser, Goran Neshich. 2006-03-31. Predicting enzyme class from protein structure using Bayesian classification.. https://pubmed.ncbi.nlm.nih.gov/16755510/

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