02122nas a2200193   4500008004100000245016100041210006900202260000800271300001000279490000700289520137600296100001501672700001801687700001501705700003301720700001901753700002601772856013001798       2016                        eng d00aBuilding and analysis of protein-protein interactions related to diabetes mellitus using support vector machine, biomedical text mining and network analysis0 aBuilding and analysis of proteinprotein interactions related to   cDEC  a37-440 v653 aIn order to understand the molecular mechanism underlying any disease, knowledge about the interacting proteins in the disease pathway is essential. The number of revealed protein-protein interactions (PPI) is still very limited compared to the available protein sequences of different organisms. Experiment based high-throughput technologies though provide some data about these interactions, those are often fairly noisy. Computational techniques for predicting protein protein interactions therefore assume significance. 1296 binary fingerprints that encode a combination of structural and geometric properties were developed using the crystallographic data of 15,000 protein complexes in the pdb server. In a case study, these fingerprints were created for proteins implicated in the Type 2 diabetes mellitus disease. The fingerprints were input into a SVM based model for discriminating disease proteins from non disease proteins yielding a classification accuracy of 78.2% (AUC value of 0.78) on an external data set composed of proteins retrieved via text mining of diabetes related literature. A PPI network was constructed and analysed to explore new disease targets. The integrated approach exemplified here has a potential for identifying disease related proteins, functional annotation and other proteomics studies. (C) 2016 Elsevier Ltd. All rights reserved.1 aVyas, Renu1 aBapat, Sanket1 aJain, Esha1 aKarthikeyan, Muthukumarasamy1 aTambe, Sanjeev1 aKulkarni, Bhaskar, D.  uhttps://library.ncl.res.in/content/building-and-analysis-protein-protein-interactions-related-diabetes-mellitus-using-support