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Sci. Signal., 26 February 2013
Vol. 6, Issue 264, p. rs5
[DOI: 10.1126/scisignal.2003629]

RESEARCH RESOURCES

Protein Complex–Based Analysis Framework for High-Throughput Data Sets

Arunachalam Vinayagam1*, Yanhui Hu1,2{dagger}, Meghana Kulkarni1{dagger}{ddagger}, Charles Roesel2,3, Richelle Sopko1, Stephanie E. Mohr1,2, and Norbert Perrimon1,2,4*

1 Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.
2 Drosophila RNAi Screening Center, Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
3 Bioinformatics Program, Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA.
4 Howard Hughes Medical Institute, Boston, MA 02115, USA.

{dagger} These authors contributed equally as second authors.

{ddagger} Present address: Belfer Institute, Dana-Farber Cancer Institute, Boston, MA 02115, USA.

Abstract: Analysis of high-throughput data increasingly relies on pathway annotation and functional information derived from Gene Ontology. This approach has limitations, in particular for the analysis of network dynamics over time or under different experimental conditions, in which modules within a network rather than complete pathways might respond and change. We report an analysis framework based on protein complexes, which are at the core of network reorganization. We generated a protein complex resource for human, Drosophila, and yeast from the literature and databases of protein-protein interaction networks, with each species having thousands of complexes. We developed COMPLEAT (http://www.flyrnai.org/compleat), a tool for data mining and visualization for complex-based analysis of high-throughput data sets, as well as analysis and integration of heterogeneous proteomics and gene expression data sets. With COMPLEAT, we identified dynamically regulated protein complexes among genome-wide RNA interference data sets that used the abundance of phosphorylated extracellular signal–regulated kinase in cells stimulated with either insulin or epidermal growth factor as the output. The analysis predicted that the Brahma complex participated in the insulin response.

* To whom correspondence should be addressed. E-mail: vinu{at}genetics.med.harvard.edu (A.V.); perrimon{at}receptor.med.harvard.edu (N.P.)

Citation: A. Vinayagam, Y. Hu, M. Kulkarni, C. Roesel, R. Sopko, S. E. Mohr, N. Perrimon, Protein Complex–Based Analysis Framework for High-Throughput Data Sets. Sci. Signal. 6, rs5 (2013).

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