Bioinformatics Advance Access originally published online on July 5, 2005
Bioinformatics 2005 21(17):3548-3557; doi:10.1093/bioinformatics/bti567
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Local modeling of global interactome networks

1Department of Biostatistics, Harvard School of Public Health Boston, MA 02115, USA
2Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, and Department of Genetics, Harvard Medical School Boston, MA 02115, USA
3Program in Computational Biology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center Seattle, WA 98109, USA
*To whom correspondence should be addressed.
Motivation: Systems biology requires accurate models of protein complexes, including physical interactions that assemble and regulate these molecular machines. Yeast two-hybrid (Y2H) and affinitypurification/mass-spectrometry (APMS) technologies measure different proteinprotein relationships, and issues of completeness, sensitivity and specificity fuel debate over which is best for high-throughput interactome data collection. Static graphs currently used to model Y2H and APMS data neglect dynamic and spatial aspects of macromolecular complexes and pleiotropic protein function.
Results: We apply the local modeling methodology proposed by Scholtens and Gentleman (2004) to two publicly available datasets and demonstrate its uses, interpretation and limitations. Specifically, we use this technology to address four major issues pertaining to proteinprotein networks. (1) We motivate the need to move from static global interactome graphs to local protein complex models. (2) We formally show that accurate local interactome models require both Y2H and APMS data, even in idealized situations. (3) We briefly discuss experimental design issues and how bait selection affects interpretability of results. (4) We point to the implications of local modeling for systems biology including functional annotation, new complex prediction, pathway interactivity and coordination with gene-expression data.
Availability: The local modeling algorithm and all protein complex estimates reported here can be found in the R package apComplex, available at http://www.bioconductor.org
Contact: dscholtens{at}northwestern.edu
Supplementary information: http://daisy.prevmed.northwestern.edu/~denise/pubs/LocalModeling
Received on January 31, 2005; revised on June 13, 2005; accepted on June 28, 2005
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