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Mining DNA microarray data using a novel approach based on graph theory
Author(s) -
del Rio Gabriel,
Bartley Theodore F,
del-Rio Heberto,
Rao Rammohan,
Jin KunLin,
Greenberg David A,
Eshoo Mark,
Bredesen Dale E
Publication year - 2001
Publication title -
febs letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.593
H-Index - 257
eISSN - 1873-3468
pISSN - 0014-5793
DOI - 10.1016/s0014-5793(01)03165-9
Subject(s) - computational biology , identification (biology) , computer science , annotation , biological pathway , graph , systems biology , biology , bioinformatics , gene , theoretical computer science , artificial intelligence , genetics , gene expression , botany
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.