PREDICT-2ND: a tool for generalized protein local structure prediction.

ABSTRACT:

Motivation

Predictions of protein local structure, derived from sequence alignment information alone, provide visualization tools for biologists to evaluate the importance of amino acid residue positions of interest in the absence of X-ray crystal/NMR structures or homology models. They are also useful as inputs to sequence analysis and modeling tools, such as hidden Markov models (HMMs), which can be used to search for homology in databases of known protein structure. In addition, local structure predictions can be used as a component of cost functions in genetic algorithms that predict protein tertiary structure. We have developed a program (predict-2nd) that trains multilayer neural networks and have applied it to numerous local structure alphabets, tuning network parameters suc

SUBMITTER: Katzman S 

PROVIDER: S-EPMC2732275 | biostudies-literature | 2008 Nov

REPOSITORIES: biostudies-literature