title: A matrix-based multilevel approach to identify functional protein modules.
abstract: Identifying functional modules is believed to reveal most cellular processes. There have been many computational approaches to investigate the underlying biological structures (Bader and Hogue, 2003; Dhillon et al., 2005; Krogan et al., 2006; Ramadan et al., 2005; Xiong et al., 2005; Zhang et al., 2004). A spectral clustering method plays a critical role identifying functional modules in a yeast protein-protein network (Ramadan et al., 2005). We present an unweighted-graph version of a multilevel spectral algorithm which more accurately identifies protein complexes with less computational time.
authors.affiliation: Department of Computer Science, The University of Iowa, Iowa City, IA 52242, USA. oliveira@cs.uiowa.edu
authors.forename: Suely
authors.initials: S
authors.lastname: Oliveira
authors.forename: Sang-Cheol
authors.initials: SC
authors.lastname: Seok
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008954:Models, Biological; D005810:Multigene Family / Q000502:physiology*; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D020543:Proteome