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PubMed · 11741594

Mining DNA microarray data using a novel approach based on graph theory.

G del Rio·T F Bartley·H del-Rio·R Rao·K L Jin·D A Greenberg·M Eshoo·D E Bredesen
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Abstract

The recent demonstration that biochemical pathways from diverse organisms are arranged in scale-free, rather than random, systems [Jeong et al., Nature 407 (2000) 651-654], emphasizes the importance of developing methods for the identification of biochemical nexuses--the nodes within biochemical pathways that serve as the major input/output hubs, and therefore represent potentially important targets for modulation. Here we describe a bioinformatics approach that identifies candidate nexuses for biochemical pathways without requiring functional gene annotation; we also provide proof-of-principle experiments to support this technique. This approach, called Nexxus, may lead to the identification of new signal transduction pathways and targets for drug design.

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ApoptosisBrain IschemiaCitric Acid CycleComputational BiologyDNA FingerprintingDatabases, FactualModels, TheoreticalOligonucleotide Array Sequence AnalysisProtein BindingSaccharomyces cerevisiaeJournal ArticleResearch Support, U.S. Gov't, P.H.S.

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G del Rio, T F Bartley, H del-Rio, R Rao, K L Jin, D A Greenberg, M Eshoo, D E Bredesen. 2001-12-07. Mining DNA microarray data using a novel approach based on graph theory.. https://doi.org/10.1016/s0014-5793(01)03165-9

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