Genome-scale identification of Legionella pneumophila effectors using a machine learning approach.

ABSTRACT: A large number of highly pathogenic bacteria utilize secretion systems to translocate effector proteins into host cells. Using these effectors, the bacteria subvert host cell processes during infection. Legionella pneumophila translocates effectors via the Icm/Dot type-IV secretion system and to date, approximately 100 effectors have been identified by various experimental and computational techniques. Effector identification is a critical first step towards the understanding of the pathogenesis system in L. pneumophila as well as in other bacterial pathogens. Here, we formulate the task of effector identification as a classification problem: each L. pneumophila open reading frame (ORF) was classified as either effector or not. We computationally defined a set of features that best disting

SUBMITTER: Burstein D 

PROVIDER: S-EPMC2701608 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature