RONN: the bio-basis function neural network technique applied to the detection of natively disordered regions in proteins

被引:510
作者
Yang, ZR
Thomson, R
McNeil, P
Esnouf, RM [1 ]
机构
[1] Univ Exeter, Sch Engn & Comp Sci, Exeter EX4 41QF, Devon, England
[2] Univ Oxford, Div Struct Biol, Oxford OX3 7BN, England
[3] Univ Oxford, Oxford Prot Prod Facil, Oxford OX3 7BN, England
[4] European Bioinformat Inst, Cambridge CB10 1SD, England
基金
英国医学研究理事会;
关键词
D O I
10.1093/bioinformatics/bti534
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:3369 / 3376
页数:8
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