Protein sequence analysis using relational soft clustering algorithms
International Journal of Computer Mathematics - Bioinformatics
Swarm optimized organizing map (SWOM): A swarm intelligence basedoptimization of self-organizing map
Expert Systems with Applications: An International Journal
Predicting palmitoylation sites using a regularised bio-basis function neural network
ISBRA'07 Proceedings of the 3rd international conference on Bioinformatics research and applications
Enhancing protein disorder detection by refined secondary structure prediction
BIRD'07 Proceedings of the 1st international conference on Bioinformatics research and development
Bio-kernel self-organizing map for HIV drug resistance classification
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Prediction of disorder with new computational tool: BVDEA
Expert Systems with Applications: An International Journal
Diagnosis of Several Diseases by Using Combined Kernels with Support Vector Machine
Journal of Medical Systems
Relevant and Non-Redundant Amino Acid Sequence Selection for Protein Functional Site Identification
International Journal of Software Science and Computational Intelligence
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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. Availability: RONN is available at http://www.strubi.ox.ac.uk/RONN. Requests for the RONN software and the database of disorder (XML format) can be directed to the corresponding author. Contact: robert@strubi.ox.ac.uk Supplementary information: Details of all predictions made during blind testing, also available at http://www.strubi.ox.ac.uk/RONN3_Supplementary.pdf