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Type III secretion systems (T3SSs) are bacterial membrane-embedded nanomachines that allow a number of human, plant, and animal pathogens to inject virulence factors directly into the cytoplasm of eukaryotic cells. Export of effectors through T3SSs is critical for motility and virulence of many major Gram-negative pathogens.

DeepT3 2.0 is a web server that integrates different deep learning models for genome-wide predicting T3SEs from a bacterium of interest. Six deep learning architectures including convolutional, recurrent, convolutional-recurrent and multilayer neural networks are intrgrated to learn N-terminal representations of proteins specifically for T3SEs prediction. Outcomes from the different models are processed for discriminating T3SEs and non-T3SEs.

Using this server, the sequences in FASTA format could be predicted by the 6 models and a final prediction will be generated according to the 6 outputs. All of the information will be listed in the table below.

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There are two ways for uploading the datasets, one is uploading a FASTA file by dragging file or clicking the button in the left box, another is typing the FASTA sequences after click

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Jiesi Luo

Department of Pharmacology,
School of Pharmacy,
Southwest Medical University,
Luzhou 646000

Runyu Jing

School of Cyber Science and Engineering,
Sichuan University,
Chengdu 610207