From E-MAPs to module maps: dissecting quantitative genetic interactions using physical interactions.
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.
Ulitsky
Igor
I
School of Computer Science, Tel Aviv University, Ramat Aviv, Israel.
Shlomi
Tomer
T
Kupiec
Martin
M
Shamir
Ron
R
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
D029701:Saccharomyces cerevisiae Proteins; D046988:Proteasome Endopeptidase Complex