Journal
SCIENCE SIGNALING
Volume 6, Issue 264, Pages -Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/scisignal.2003629
Keywords
-
Categories
Funding
- Dana-Farber/Harvard Cancer Center [P30-CA06516]
- Leukemia and Lymphoma Society
- [P01-CA120964]
- [R01-GM067761]
- [R01-DK088718]
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available