QNet: a tool for querying protein interaction networks.
Molecular interaction databases can be used to study the evolution of molecular pathways across species. Querying such pathways is a challenging computational problem, and recent efforts have been limited to simple queries (paths), or simple networks (forests). In this paper, we significantly extend the class of pathways that can be efficiently queried to the case of trees, and graphs of bounded treewidth. Our algorithm allows the identification of non-exact (homeomorphic) matches, exploiting the color coding technique of Alon et al. (1995). We implement a tool for tree queries, called QNet, and test its retrieval properties in simulations and on real network data. We show that QNet searches queries with up to nine proteins in seconds on current networks, and outperforms sequence-based searches. We also use QNet to perform the first large-scale cross-species comparison of protein complexes, by querying known yeast complexes against a fly protein interaction network. This comparison points to strong conservation between the two species, and underscores the importance of our tool in mining protein interaction networks.
Dost
Banu
B
Computer Science and Engineering, University of California, San Diego, California, USA. bdost@cs.ucsd.edu
Shlomi
Tomer
T
Gupta
Nitin
N
Ruppin
Eytan
E
Bafna
Vineet
V
Sharan
Roded
R
D000465:Algorithms; D000818:Animals; D019295:Computational Biology; D003198:Computer Simulation; D030562:Databases, Protein; D004331:Drosophila melanogaster; D019143:Evolution, Molecular; D006801:Humans; D020935:MAP Kinase Signaling System / Q000502:physiology; D008433:Mathematics; D008954:Models, Biological; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000378:metabolism*; D012984:Software
D011506:Proteins