A comprehensive assessment of sequence-based and template-based methods for protein contact prediction.

ABSTRACT:

Motivation

Pair-wise residue-residue contacts in proteins can be predicted from both threading templates and sequence-based machine learning. However, most structure modeling approaches only use the template-based contact predictions in guiding the simulations; this is partly because the sequence-based contact predictions are usually considered to be less accurate than that by threading. With the rapid progress in sequence databases and machine-learning techniques, it is necessary to have a detailed and comprehensive assessment of the contact-prediction methods in different template conditions.

Results

We develop two methods for protein-contact predictions: SVM-SEQ is a sequence-based machine learning approach which trains a variety of sequence-derived features on contact ma

SUBMITTER: Wu S 

PROVIDER: S-EPMC2648832 | biostudies-literature | 2008 Apr

REPOSITORIES: biostudies-literature