Gene Reachability Using Page Ranking on Gene Co-expression Networks
We modify the Google Page-Rank algorithm, which is primarily used for ranking web pages, to analyze the gene reachability in complex gene co-expression networks. Our modification is based on the average connections per gene. We propose a new method to compute the metric of average connections per gene, inspired by the Page-Rank algorithm. We calculate this average as eight for human genome data and three to seven for yeast genome data. Our algorithm provides clustering of genes. The proposed analogy between web pages and genes may offer a new way to interpret gene networks.
KeywordsIngenuity Pathway Analysis Gene Ranking Connectivity Information Average Connection Gene Connection
The work of W. Zhang was supported by the NSF grants IIS-0535257 and DBI-0743797 and a grant from the Alzheimer’s Association. The work of J. P. Cobb was supported by the NIH grants R21GM075023 and R01GM59960.
- 1.S. Brin and L. Page. The anatomy of a large-scale hypertextual Web search engine (http://www-db.stanford.edu/backrub/google.html), Proceedings of 7th Intlernational Conference of World Wide Web 7, pages 107–117, 1998.
- 2.J. Ruan and W. Zhang. Identification and evaluation of functional modules in gene co-expression networks, RECOMB Satellite Conferences on Systems Biology and Computational Proteomics, San Diego, CA, Dec. 2006.Google Scholar
- 4.J. E. McDunn, K. D. Husain, A. D. Polpitiya, A. Burykin. J. Ruan, Q. Li, W. Schierding, N. Lin, D. Dixon, W. Zhang, C. M. Coopersmith, W. M. Dunne, M. Colonna, B. K. Ghosh, and J. P. Cobb. Plasticity of the systematic inflammatory response to acute infection during critical illness: Development of the riboleukogram, PLoS One, 3(2):e1564, 2008.PubMedCrossRefGoogle Scholar