Finding friends and enemies in an enemies-only network: A graph diffusion kernel for predicting novel genetic interactions and co-complex membership from yeast genetic interactions

Yan Qi, Yasir Suhail, Yu Yi Lin, Jef D. Boeke, Joel S. Bader

    Research output: Contribution to journalArticle

    Abstract

    The yeast synthetic lethal genetic interaction network contains rich information about underlying pathways and protein complexes as well as new genetic interactions yet to be discovered. We have developed a graph diffusion kernel as a unified framework for inferring complex/pathway membership analogous to "friends" and genetic interactions analogous to "enemies" from the genetic interaction network. When applied to the Saccharomyces cerevisiae synthetic lethal genetic interaction network, we can achieve a precision around 50% with 20% to 50% recall in the genome-wide prediction of new genetic interactions, supported by experimental validation. The kernels show significant improvement over previous best methods for predicting genetic interactions and protein co-complex membership from genetic interaction data.

    Original languageEnglish (US)
    Pages (from-to)1991-2004
    Number of pages14
    JournalGenome Research
    Volume18
    Issue number12
    DOIs
    StatePublished - Dec 2008

    ASJC Scopus subject areas

    • Genetics
    • Genetics(clinical)

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