title: From E-MAPs to module maps: dissecting quantitative genetic interactions using physical interactions.
abstract: Recent technological breakthroughs allow the quantification of hundreds of thousands of genetic interactions (GIs) in Saccharomyces cerevisiae. The interpretation of these data is often difficult, but it can be improved by the joint analysis of GIs along with complementary data types. Here, we describe a novel methodology that integrates genetic and physical interaction data. We use our method to identify a collection of functional modules related to chromosomal biology and to investigate the relations among them. We show how the resulting map of modules provides clues for the elucidation of function both at the level of individual genes and at the level of functional modules.
authors.affiliation: School of Computer Science, Tel Aviv University, Ramat Aviv, Israel.
authors.forename: Igor
authors.initials: I
authors.lastname: Ulitsky
authors.forename: Tomer
authors.initials: T
authors.lastname: Shlomi
authors.forename: Martin
authors.initials: M
authors.lastname: Kupiec
authors.forename: Ron
authors.initials: R
authors.lastname: Shamir
mesh_terms: D002467:Cell Nucleus / Q000378:metabolism; D004843:Epistasis, Genetic; D008938:Mitosis; D010641:Phenotype; D016062:Porosity; D046988:Proteasome Endopeptidase Complex; D011485:Protein Binding; D012441:Saccharomyces cerevisiae / Q000235:genetics* / Q000378:metabolism*; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics* / Q000378:metabolism*; D008941:Spindle Apparatus / Q000378:metabolism
chemical_list: D029701:Saccharomyces cerevisiae Proteins; D046988:Proteasome Endopeptidase Complex