Computational discovery of gene modules and regulatory networks Export

@article{citeulike:163573, abstract = {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}, address = {MIT Computer Science and Artificial Intelligence Laboratory, 200 Technology Square, Cambridge, Massachusetts 02139, USA.}, author = {Bar-Joseph, Ziv and Gerber, Georg K. and Lee, Tong I. and Rinaldi, Nicola J. and Yoo, Jane Y. and Robert, Francois and Gordon, D. Benjamin and Fraenkel, Ernest and Jaakkola, Tommi S. and Young, Richard A. and Gifford, David K.}, citeulike-article-id = {163573}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/nbt890}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/nbt890}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/14555958}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=14555958}, day = {12}, doi = {10.1038/nbt890}, issn = {1087-0156}, journal = {Nat Biotech}, keywords = {chip-chip, expression, regulation}, month = {October}, number = {11}, pages = {1337--1342}, posted-at = {2006-06-30 13:03:05}, priority = {2}, publisher = {Nature Publishing Group}, title = {Computational discovery of gene modules and regulatory networks}, url = {http://dx.doi.org/10.1038/nbt890}, volume = {21}, year = {2003} }

TY - JOUR ID - citeulike:163573 L3 - citeulike-article-id:163573 N2 - 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 IS - 11 JF - Nat Biotech SN - 1087-0156 AD - MIT Computer Science and Artificial Intelligence Laboratory, 200 Technology Square, Cambridge, Massachusetts 02139, USA. EP - 1342 TI - Computational discovery of gene modules and regulatory networks PB - Nature Publishing Group VL - 21 SP - 1337 KW - chip-chip KW - expression KW - regulation AU - Bar-Joseph, Ziv AU - Gerber, Georg AU - Lee, Tong AU - Rinaldi, Nicola AU - Yoo, Jane AU - Robert, Francois AU - Gordon, Benjamin AU - Fraenkel, Ernest AU - Jaakkola, Tommi AU - Young, Richard AU - Gifford, David PY - 2003/10/12/ UR - http://dx.doi.org/10.1038/nbt890 ER -