Mining DNA microarray data using a novel approach based on graph theory.
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.
del Rio
G
G
The Buck Institute for Age Research, 8001 Redwood Blvd., Novato, CA 94945, USA.
Bartley
T F
TF
del-Rio
H
H
Rao
R
R
Jin
K L
KL
Greenberg
D A
DA
Eshoo
M
M
Bredesen
D E
DE
D017209:Apoptosis / Q000502:physiology; D002545:Brain Ischemia / Q000378:metabolism; D002952:Citric Acid Cycle; D019295:Computational Biology / Q000379:methods*; D016172:DNA Fingerprinting / Q000379:methods*; D016208:Databases, Factual; D008962:Models, Theoretical; D020411:Oligonucleotide Array Sequence Analysis; D011485:Protein Binding; D012441:Saccharomyces cerevisiae / Q000502:physiology