Probabilistic grammatical model for helix-helix contact site classification.

ABSTRACT:

Background

Hidden Markov Models power many state-of-the-art tools in the field of protein bioinformatics. While excelling in their tasks, these methods of protein analysis do not convey directly information on medium- and long-range residue-residue interactions. This requires an expressive power of at least context-free grammars. However, application of more powerful grammar formalisms to protein analysis has been surprisingly limited.

Results

In this work, we present a probabilistic grammatical framework for problem-specific protein languages and apply it to classification of transmembrane helix-helix pairs configurations. The core of the model consists of a probabilistic context-free grammar, automatically inferred by a genetic algorithm from only a generic set of expert-b

SUBMITTER: Dyrka W 

PROVIDER: S-EPMC3892132 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature