alexa Association Analysis Of Type 2 Diabetes Proteins Interaction Network
ISSN: 0974-276X

Journal of Proteomics & Bioinformatics
Open Access

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4th International Conference on Proteomics & Bioinformatics
August 04-06, 2014 Hilton-Chicago/Northbrook, Chicago, USA

Kudipudi Srinivas
ScientificTracks Abstracts: J Proteomics Bioinform
DOI: 10.4172/0974-276X.S1.071
Abstract
Association analysis of data mining identifies relationships or affinities between entities. Type 2 Diabetes is a chronic progressive disease and the most common form of diabetes, accounting for 85 to 95 percent of the total number of diabetes cases in developed countries and an even higher percentage in developing countries. Using data mining techniques, especially association analysis, mine the protein interaction networks and domains related to type 2 diabetes, and discover some regulation elements that are essential to the expression of proteins. Drug discovery and testing of particular disease requires preclinical and clinical trials. The drug discovery process is labour intensive and expensive. For eradicating such hurdles and paving the way for the drugs of future, in silico methods have been envisaged here to study the relation between type 2 diabetes proteins and drug targets using the advanced concepts of data mining and bioinformatics.
Biography
Kudipudi Srinivas received his PhD in Computer Science and Engineering from Acharya Nagarjuna University, India, and M.Tech (CSE) from JNTU Kakinada. Currently he is working as a Professor in the department of Computer Science and engineering, V.R Siddhartha Engineering College, Vijayawada, India. He has published 18 international papers and 2 monograms in reputed journals. He is the co-principal Investigator for the project ?Mining Alzheimer?s Disease Signal Transduction Modulatory Drug Target Networks?. His research interest includes Data mining, Bioinformatics and Digital image processing
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