Improving protein secondary structure prediction using a simple k-mer model.

ABSTRACT:

Motivation

Some first order methods for protein sequence analysis inherently treat each position as independent. We develop a general framework for introducing longer range interactions. We then demonstrate the power of our approach by applying it to secondary structure prediction; under the independence assumption, sequences produced by existing methods can produce features that are not protein like, an extreme example being a helix of length 1. Our goal was to make the predictions from state of the art methods more realistic, without loss of performance by other measures.

Results

Our framework for longer range interactions is described as a k-mer order model. We succeeded in applying our model to the specific problem of secondary structure prediction, to be used as an addi

SUBMITTER: Madera M 

PROVIDER: S-EPMC2828123 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature