PSP_MCSVM: brainstorming consensus prediction of protein secondary structures using two-stage multiclass support vector machines.

ABSTRACT: Secondary structure prediction is a crucial task for understanding the variety of protein structures and performed biological functions. Prediction of secondary structures for new proteins using their amino acid sequences is of fundamental importance in bioinformatics. We propose a novel technique to predict protein secondary structures based on position-specific scoring matrices (PSSMs) and physico-chemical properties of amino acids. It is a two stage approach involving multiclass support vector machines (SVMs) as classifiers for three different structural conformations, viz., helix, sheet and coil. In the first stage, PSSMs obtained from PSI-BLAST and five specially selected physicochemical properties of amino acids are fed into SVMs as features for sequence-to-structure prediction. Conf

SUBMITTER: Chatterjee P 

PROVIDER: S-EPMC3168739 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature