Computational discovery of gene modules and regulatory networks.
We describe an algorithm for discovering regulatory networks of gene modules, GRAM (Genetic Regulatory Modules), that combines information from genome-wide location and expression data sets. A gene module is defined as a set of coexpressed genes to which the same set of transcription factors binds. Unlike previous approaches that relied primarily on functional information from expression data, the GRAM algorithm explicitly links genes to the factors that regulate them by incorporating DNA binding data, which provide direct physical evidence of regulatory interactions. We use the GRAM algorithm to describe a genome-wide regulatory network in Saccharomyces cerevisiae using binding information for 106 transcription factors profiled in rich medium conditions data from over 500 expression experiments. We also present a genome-wide location analysis data set for regulators in yeast cells treated with rapamycin, and use the GRAM algorithm to provide biological insights into this regulatory network
Bar-Joseph
Ziv
Z
MIT Computer Science and Artificial Intelligence Laboratory, 200 Technology Square, Cambridge, Massachusetts 02139, USA.
Gerber
Georg K
GK
Lee
Tong Ihn
TI
Rinaldi
Nicola J
NJ
Yoo
Jane Y
JY
Robert
François
F
Gordon
D Benjamin
DB
Fraenkel
Ernest
E
Jaakkola
Tommi S
TS
Young
Richard A
RA
Gifford
David K
DK
D000465:Algorithms; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods; D015966:Gene Expression Regulation, Fungal / Q000502:physiology*; D016681:Genome, Fungal; D008957:Models, Genetic; D012045:Regulatory Sequences, Nucleic Acid / Q000235:genetics; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics* / Q000378:metabolism*; D014157:Transcription Factors / Q000235:genetics* / Q000378:metabolism*; D014158:Transcription, Genetic / Q000502:physiology*
D029701:Saccharomyces cerevisiae Proteins; D014157:Transcription Factors