Box-plot-and-instance representation of percentages of pEffect-predicted type III effectors

pEffect

Box-plot-and-instance representation of percentages of pEffect-predicted type III effectors

pEffect

The type III secretion system is one of the causes of a wide range of bacterial infections in human, animals and plants. This system comprises a hollow needle-like structure localized on the surface of bacterial cells that injects specific bacterial proteins, the so-called effectors, directly into the cytoplasm of a host cell. During infection, effectors convert host resources to their advantage and promote pathogenicity.

We - Tatyana Goldberg, Burkhard Rost and Yana Bromberg - at BrombergLab and RostLab developed a novel method, pEffect that predicts bacterial type III effector proteins. In our method, we combine sequence-based homology searches (through PSI-BLAST) with advanced machine learning (Profile Kernel Support Vector Machines) to accurately predict effector proteins. We use information encoded in the entire protein sequence for our predictions.

If you find pEffect useful please cite us!

Download: Proteome predictions, data sets used and the standalone version of pEffect

Avatar
Tatyana Goldberg
PhD Student

I am a proud former scholar of the Ernst Ludwig Ehrlich Studienwerk and also a guest editor of the F1000Research BioJS channel