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This article is part of the supplement: Highlights from the Seventh International Society for Computational Biology (ISCB) Student Council Symposium 2011

Open Access Poster presentation

Computational analysis of genetic network involved in pancreatic cancer in human

Mrinal Mishra* and Ambuj Kumar

  • * Corresponding author: Mrinal Mishra

Author Affiliations

School of Bio Sciences and Technology, VIT University, Vellore, India

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BMC Bioinformatics 2011, 12(Suppl 11):A11  doi:10.1186/1471-2105-12-S11-A11

The electronic version of this article is the complete one and can be found online at:

Published:21 November 2011

© 2011 Mishra and Kumar; licensee BioMed Central Ltd.

This is an open access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Poster presentation

The poster is based on the in silico identification and analysis of the variation in the gene network related to the pancreatic cancer. Pancreatic cancer has been a major cause of death in Asia and European countries. This cancer is not easily detectable in its initial stages and at the later stages it becomes very hard to cure this disease. So the in-depth understanding of the variation in the genetic pathway of this disease is very important. We selected 5 candidate genes from various published journals which are involved in the pancreatic cancer pathway (KRAS, CDKN2A, MADH4, TP53 and ARMET) in generating their interaction network using Agilent literature search plugin in cytoscape. The organic layout of interaction revealed the cross interaction between these genes and the other neighbour genes. Merging the expression profile data of the pancreatic cancer to the parent network helped us in understanding the variation of the network in the diseased state. Using the merged profile network we found out the importance of the KRAS & CDKN2A gene interaction with other 21 neighbour genes among which PIK3CA and TP53 interactions were showing major variation on their expression pattern. This study reveals the importance of change in expression level of candidate genes(KRAS,CDKN2A and TP53) in causing pancreatic cancer. The results obtained in our study will be very much useful in detecting the disease in its initial stages and in finding the cure.