Prediction of protein binding sites in protein structures using hidden Markov support vector machine.

ABSTRACT:

Background

Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. Recent research on protein binding site prediction has been mainly based on widely known machine learning techniques, such as artificial neural networks, support vector machines, conditional random field, etc. However, the prediction performance is still too low to be used in practice. It is necessary to explore new algorithms, theories and features to further improve the performance.

Results

In this study, we introduce a novel machine learning model hidden Markov support vector machine for protein binding site prediction. The model treats the protein binding site prediction as a sequential labelling task based on the maximum margin criterion. Commo

SUBMITTER: Liu B 

PROVIDER: S-EPMC2785799 | biostudies-literature | 2009 Nov

REPOSITORIES: biostudies-literature