MOTIVATION: Recent studies have found many proteins containing regions that do not form well-defined three-dimensional structures in their native states. The study and detection of such disordered regions is important both for understanding protein function and for facilitating structural analysis since disordered regions may affect solubility and/or crystallizability. RESULTS: We have developed the regional order neural network (RONN) software as an application of our recently developed 'bio-basis function neural network' pattern recognition algorithm to the detection of natively disordered regions in proteins. The results of blind-testing a panel of nine disorder prediction tools (including RONN) against 80 protein sequences derived from the Protein Data Bank shows that, based on the probability excess measure, RONN performed the best.

Original publication

DOI

10.1093/bioinformatics/bti534

Type

Journal article

Journal

Bioinformatics (Oxford, England)

Publication Date

08/2005

Volume

21

Pages

3369 - 3376

Addresses

School of Engineering and Computer Science, Exeter University, Exeter EX4 4QF, UK.

Keywords

Proteins, Models, Statistical, Sequence Alignment, Sequence Analysis, Protein, Amino Acid Sequence, Protein Conformation, Protein Folding, Structure-Activity Relationship, Algorithms, Neural Networks (Computer), Models, Chemical, Models, Molecular, Computer Simulation, Software, Molecular Sequence Data, Pattern Recognition, Automated