Conference paper
Comprehensive analyses of tumor suppressor genes in protein-protein interaction networks: A topological perspective
Proceedings of the 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, pp.101-102
IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS), 2012 (Washington DC, United States, 02-Dec-2012–04-Dec-2012)
IEEE Publishing Inc.
2012
Abstract
Tumor suppressor genes (TSGs) are a class of genes that play key roles in cancer induction and development. A comprehensive investigation of TSGs in protein-protein interaction (PPI) networks may expand our understanding on their roles in cancer development. In this study, we first collected reliable human TSG lists from tumor suppressor gene database. To provide an unbiased network view, we mapped human TSGs to four model organisms with different evolutionary distances to human (mouse, fly, worm, and yeast) using homology relationship. Using human TSGs and their homologs, we overlapped TSGs to their corresponding PPI networks. To explore the network properties of TSGs we examined their degree, betweenness, and closeness centralities by uniquely comparing them with three other sets of genes. We found that TSGs tend to interact more strongly than other non-cancer disease genes in human, mouse, fly, and worm, which confirmed previous global topological property studies on cancer genes. This demonstrates that TSGs are important to initiate interaction with other molecular during cancer development. This study represents the first statistical evaluation of TSGs in PPI networks. In addition, the data presented in this study will be valuable for the study of TSGs and their interaction partners. © 2012 IEEE.
Details
- Title
- Comprehensive analyses of tumor suppressor genes in protein-protein interaction networks: A topological perspective
- Authors
- Min Zhao (Author) - Vanderbilt University School of Medicine, United StatesJ Sun (Author) - Vanderbilt University School of Medicine, United StatesZ Zhao (Author) - Vanderbilt University School of Medicine, United States
- Publication details
- Proceedings of the 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, pp.101-102
- Conference details
- IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS), 2012 (Washington DC, United States, 02-Dec-2012–04-Dec-2012)
- Publisher
- IEEE Publishing Inc.
- Date published
- 2012
- DOI
- 10.1109/GENSIPS.2012.6507738
- ISBN
- 9781467352369
- Copyright note
- Copyright © 2010 IEEE Publishing Inc. The accepted version of this manuscript is reproduced here in accordance with the copyright policy of the publisher..
- Organisation Unit
- School of Science and Engineering - Legacy; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 99448771002621
- Output Type
- Conference paper
- Research Statement
- false
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