MOTIVATION: With the growing availability of high-throughput protein-protein interaction (PPI) data, it has become possible to consider how a protein's local or global network characteristics predict its function. RESULTS: We introduce a graph-theoretic approach that identifies key regulatory proteins in an organism by analyzing proteins' local PPI network structure. We apply the method to the yeast genome and describe several properties of the resulting set of regulatory hubs. Finally, we demonstrate how the identified hubs and putative target gene sets can be used to identify causative, functional regulators of differential gene expression linked to human disease. AVAILABILITY: Code is available at http://bcb.cs.tufts.edu/hubcomps. CONTACT: fox.andrew.d@gmail.com; slonim@cs.tufts.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: With the growing availability of high-throughput protein-protein interaction (PPI) data, it has become possible to consider how a protein's local or global network characteristics predict its function. RESULTS: We introduce a graph-theoretic approach that identifies key regulatory proteins in an organism by analyzing proteins' local PPI network structure. We apply the method to the yeast genome and describe several properties of the resulting set of regulatory hubs. Finally, we demonstrate how the identified hubs and putative target gene sets can be used to identify causative, functional regulators of differential gene expression linked to human disease. AVAILABILITY: Code is available at http://bcb.cs.tufts.edu/hubcomps. CONTACT: fox.andrew.d@gmail.com; slonim@cs.tufts.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: T Ito; K Tashiro; S Muta; R Ozawa; T Chiba; M Nishizawa; K Yamamoto; S Kuhara; Y Sakaki Journal: Proc Natl Acad Sci U S A Date: 2000-02-01 Impact factor: 11.205
Authors: P Uetz; L Giot; G Cagney; T A Mansfield; R S Judson; J R Knight; D Lockshon; V Narayan; M Srinivasan; P Pochart; A Qureshi-Emili; Y Li; B Godwin; D Conover; T Kalbfleisch; G Vijayadamodar; M Yang; M Johnston; S Fields; J M Rothberg Journal: Nature Date: 2000-02-10 Impact factor: 49.962
Authors: Scott A Armstrong; Jane E Staunton; Lewis B Silverman; Rob Pieters; Monique L den Boer; Mark D Minden; Stephen E Sallan; Eric S Lander; Todd R Golub; Stanley J Korsmeyer Journal: Nat Genet Date: 2001-12-03 Impact factor: 38.330