A combined algorithm for genome-wide prediction of protein function

Edward M. Marcotte, Matteo Pellegrini, Michael J. Thompson, Todd O. Yeates and David Eisenberg ()
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Edward M. Marcotte: Molecular Biology Institute, UCLA-DOE Laboratory of Structural Biology and Molecular Medicine, University of California, PO Box 951570
Matteo Pellegrini: Protein Pathways
Michael J. Thompson: Molecular Biology Institute, UCLA-DOE Laboratory of Structural Biology and Molecular Medicine, University of California, PO Box 951570
Todd O. Yeates: Molecular Biology Institute, UCLA-DOE Laboratory of Structural Biology and Molecular Medicine, University of California, PO Box 951570
David Eisenberg: Molecular Biology Institute, UCLA-DOE Laboratory of Structural Biology and Molecular Medicine, University of California, PO Box 951570

Nature, 1999, vol. 402, issue 6757, 83-86

Abstract: Abstract The availability of over 20 fully sequenced genomes has driven the development of new methods to find protein function and interactions. Here we group proteins by correlated evolution1, correlated messenger RNA expression patterns2 and patterns of domain fusion3 to determine functional relationships among the 6,217 proteins of the yeast Saccharomyces cerevisiae. Using these methods, we discover over 93,000 pairwise links between functionally related yeast proteins. Links between characterized and uncharacterized proteins allow a general function to be assigned to more than half of the 2,557 previously uncharacterized yeast proteins. Examples of functional links are given for a protein family of previously unknown function, a protein whose human homologues are implicated in colon cancer and the yeast prion Sup35.

Date: 1999
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DOI: 10.1038/47048

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