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Access through your institution Buy or subscribe So, how does the GRAM algorithm work? First, it examines DNA-binding data and identifies sets of genes that are bound by common sets of
transcriptional regulators. Next, it uses expression data to identify a subset of the genes, the expression of which is highly correlated. Finally, the algorithm searches the DNA-binding
data again, using less stringent criteria, to find more genes of similar expression that are also bound by the same transcription factors. The authors put the GRAM algorithm to the test in
_Saccharomyces cerevisiae_ by applying it to genome-wide location data for 106 transcription factors and >500 expression experiments — in this way, they identified 106 sets of
co-expressed genes that are bound by the same transcription factors. These so-called gene modules contain 655 genes and are regulated by 68 transcription factors. Because gene modules link
the common expression pattern of a set of genes to a set of regulators, the authors were also able to predict that 11 of the regulators were activators — a finding that was confirmed by
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PAPER * Bar-Joseph, Z. et al. Computational discovery of gene modules and regulatory networks. _Nature Biotechnol._ 21, 1337–1342 (2003) Article CAS Google Scholar Download references
Authors * Natalie Wilson View author publications You can also search for this author inPubMed Google Scholar RELATED LINKS RELATED LINKS WEB SITES David K. Gifford's laboratory Java
implementation of the GRAM algorithm RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Wilson, N. A new algorithm weighs in. _Nat Rev Genet_ 4, 930 (2003).
https://doi.org/10.1038/nrg1234 Download citation * Issue Date: 01 December 2003 * DOI: https://doi.org/10.1038/nrg1234 SHARE THIS ARTICLE Anyone you share the following link with will be
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