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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:

Goldberg, Tatyana, Burkhard Rost, and Yana Bromberg. "Computational prediction shines light on type III secretion origins." Scientific reports 6 (2016): 34516.

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