Accurate prediction of bacterial type IV secreted effectors using amino acid composition and PSSM profiles.

ABSTRACT:

Motivation

Various human pathogens secret effector proteins into hosts cells via the type IV secretion system (T4SS). These proteins play important roles in the interaction between bacteria and hosts. Computational methods for T4SS effector prediction have been developed for screening experimental targets in several isolated bacterial species; however, widely applicable prediction approaches are still unavailable

Results

In this work, four types of distinctive features, namely, amino acid composition, dipeptide composition, .position-specific scoring matrix composition and auto covariance transformation of position-specific scoring matrix, were calculated from primary sequences. A classifier, T4EffPred, was developed using the support vector machine with these features and t

SUBMITTER: Zou L 

PROVIDER: S-EPMC5994942 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature