ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
Research Article: Exploiting three kinds of interface propensities to identify protein binding sites
Computational Biology and Chemistry
CMSB '09 Proceedings of the 7th International Conference on Computational Methods in Systems Biology
Protein interface residues recognition using granular computing theory
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Predicting v(d)j recombination using conditional random fields
PRIB'12 Proceedings of the 7th IAPR international conference on Pattern Recognition in Bioinformatics
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Motivation: We are motivated by the fast-growing number of protein structures in the Protein Data Bank with necessary information for prediction of protein--protein interaction sites to develop methods for identification of residues participating in protein--protein interactions. We would like to compare conditional random fields (CRFs)-based method with conventional classification-based methods that omit the relation between two labels of neighboring residues to show the advantages of CRFs-based method in predicting protein--protein interaction sites. Results: The prediction of protein--protein interaction sites is solved as a sequential labeling problem by applying CRFs with features including protein sequence profile and residue accessible surface area. The CRFs-based method can achieve a comparable performance with state-of-the-art methods, when 1276 nonredundant hetero-complex protein chains are used as training and test set. Experimental result shows that CRFs-based method is a powerful and robust protein--protein interaction site prediction method and can be used to guide biologists to make specific experiments on proteins. Availability: http://www.insun.hit.edu.cn/~mhli/site_CRFs/index.html Contact: mhli@insun.hit.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.