Predicting enzyme class from protein structure using Bayesian classification

Genet Mol Res. 2006 Mar 31;5(1):193-202.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Bayes Theorem*
  • Enzymes / chemistry*
  • Enzymes / classification*
  • Humans
  • Protein Conformation*
  • Sequence Alignment

Substances

  • Enzymes