T4EffPred is a web server which can predict effector proteins secreted by Type IV secretion systems of Gram-negative bacteria. This predictor was developed by computing four classes of sequence features such as amino acid composition, residue pair composition, PSSM composition and auto covariance transformation of PSMM profiles to train a SVM_based classification model. On benchmark tests, the predictor can discriminate type-IVA effectors and non-effectors with overover 93% accuracy and discriminate type-IVB effectors and non-effectors with overover 95% accuracy . It is the firstly anounced de vovo predictor which can widely predict effectors in Gram-negetive bactericial genomes.
This server is free available to any user, but without any warranty.
For using T4EffPred, Please cite:
Lingyun Zou, Chonghan Nan, Fuquan Hu. Accurate Prediction of Bacterial Type IV Secreted Effectors using Amino Acid Compositions and PSSM Profiles. Bioinformatics, 2013 Sep 23. [Epub ahead of print]
SecRet4: a web-based bacterial type IV secretion system resource.