Discovering Protein Functional Models Using Inductive Logic Programming

摘要

The paper describes a method for machine discovery of protein functional models from protein databases using Inductive Logic Programming based on top-down search for relative least general generalization. The method discovers effectively protein function models that explain the relationship between functions of proteins and their amino acid sequences described in protein databases. The method succeeds in discovering protein functional models for forty membrane proteins, which coincide with conjectured models in literature of molecular biology.