A scalable, parallel algorithm for maximal clique enumeration
Journal of Parallel and Distributed Computing
On perturbation theory and an algorithm for maximal clique enumeration in uncertain and noisy graphs
Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data
Integrative construction and analysis of condition-specific biological networks
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Theoretical underpinnings for maximal clique enumeration on perturbed graphs
Theoretical Computer Science
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Motivation and Methods: All living organisms and the survival of all cells critically depend on their ability to sense and quickly adapt to changes in the environment and to other stress conditions. We study stress response mechanisms in Saccharomyces cerevisiae by identifying genes that, according to very stringent criteria, have persistent co-expression under a variety of stress conditions. This is enabled through a fast clique search method applied to the intersection of several co-expression graphs calculated over the data of Gasch et al. This method exploits the topological characteristics of these graphs. Results: We observe cliques in the intersection graphs that are much larger than expected under a null model of changing gene identities for different stress conditions but maintaining the co-expression topology within each one. Persistent cliques are analyzed to identify enriched function as well as enriched regulation by a small number of TFs. These TFs, therefore, characterize a universal and persistent reaction to stress response. We further demonstrate that the vertices (genes) of many cliques in the intersection graphs are co-localized in the yeast genome, to a degree far beyond the random expectation. Co-localization can hypothetically contribute to a quick co-ordinated response. We propose the use of persistent cliques in further study of properties of co-regulation. Supplementary information: http://www.cs.technion.ac.il/~olegro/stress.html Contact: olegro@cs.technion.ac.il