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Computational biology

A new algorithm weighs in

Nature Reviews Genetics volume 4, page 930 (2003)Cite this article

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 previous experimental work.

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ORIGINAL RESEARCH PAPER

  1. Bar-Joseph, Z. et al. Computational discovery of gene modules and regulatory networks. Nature Biotechnol. 21, 1337–1342 (2003)

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Authors
  1. Natalie Wilson
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David K. Gifford's laboratory

Java implementation of the GRAM algorithm

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Wilson, N. A new algorithm weighs in. Nat Rev Genet 4, 930 (2003). https://doi.org/10.1038/nrg1234

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