Web Servers

An integrated deep learning framework designed to predict effector proteins of fungi and oomycetes

Maintained by Mengdi Yuan

POOE is a support vector machine-based method for predicting oomycete effectors, which use the sequence embeddings from a pre-trained large protein language model (ProtTrans) as input. POOE could achieve a highly accurate performance with an area under the precision-recall curve of 0.804 (area under the receiver operating characteristic curve = 0.893, accuracy = 0.874, precision = 0.777, recall = 0.684, and specificity= 0.936) in the five-fold cross-validation.

Maintained by Miao Zhao

DeepAraPPI is an advanced platform designed for predicting protein-protein interactions (PPIs) in Arabidopsis by harnessing sequence, domain, and Gene Ontology (GO) information. The framework of DeepAraPPI includes three integral components: (i) a word2vec encoding-based Siamese recurrent convolutional neural network (RCNN) model; (ii) a Domain2vec encoding-based multiple-layer perceptron (MLP) model; and (iii) a GO2vec encoding-based MLP model.

Maintained by Jingyan Zheng

InterSPPI (v3) is a platform that could predict protein-protein interactions (PPIs) between host and pathogens. Currently, InterSPPI includes Arabidopsis-pathogen(v1.0 & v2.0), human-bacteria and human-virus PPI prediction web server.

Maintained by Xianyi Lian