title: Building and analysis of protein-protein interactions related to diabetes mellitus using support vector machine, biomedical text mining and network analysis.
abstract: In 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.
authors.affiliation: MIT School of Bioengineering Science and Research, ADT University, Loni Kalbhor, Pune, 412201, India. Electronic address: renu.vyas@mituniversity.edu.in.
authors.forename: Renu
authors.initials: R
authors.lastname: Vyas
authors.affiliation: Digital Information Resource Centre (DIRC) & Centre of Excellence in Scientific Computing (CoESC), CSIR-National Chemical Laboratory, Pune, 411008, India.
authors.forename: Sanket
authors.initials: S
authors.lastname: Bapat
authors.affiliation: Digital Information Resource Centre (DIRC) & Centre of Excellence in Scientific Computing (CoESC), CSIR-National Chemical Laboratory, Pune, 411008, India.
authors.forename: Esha
authors.initials: E
authors.lastname: Jain
authors.affiliation: Digital Information Resource Centre (DIRC) & Centre of Excellence in Scientific Computing (CoESC), CSIR-National Chemical Laboratory, Pune, 411008, India.
authors.forename: Muthukumarasamy
authors.initials: M
authors.lastname: Karthikeyan
authors.affiliation: Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune, 411008, India.
authors.forename: Sanjeev
authors.initials: S
authors.lastname: Tambe
authors.affiliation: Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune, 411008, India.
authors.forename: Bhaskar D
authors.initials: BD
authors.lastname: Kulkarni
mesh_terms: D057225:Data Mining; D003920:Diabetes Mellitus / Q000378:metabolism*; D060066:Protein Interaction Maps; D060388:Support Vector Machine
keywords: Diabetes; Machine learning; Protein interaction network; Protein-protein interactions; SVM