title: RONN: the bio-basis function neural network technique applied to the detection of natively disordered regions in proteins.
abstract: BACKGROUND
  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.
authors.affiliation: School of Engineering and Computer Science, Exeter University, Exeter EX4 4QF, UK.
authors.forename: Zheng Rong
authors.initials: ZR
authors.lastname: Yang
authors.forename: Rebecca
authors.initials: R
authors.lastname: Thomson
authors.forename: Philip
authors.initials: P
authors.lastname: McNeil
authors.forename: Robert M
authors.initials: RM
authors.lastname: Esnouf
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D015233:Models, Statistical; D008969:Molecular Sequence Data; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000032:analysis / Q000737:chemistry* / Q000145:classification; D016415:Sequence Alignment / Q000379:methods; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins