Database List
  • PlaD [by Huan Qi]

    PlaD is a transcriptomics database for plant defense responses to pathogens. The current PlaD contains the following key features. First, it provides large-scale curated data related to plant defense responses, including gene expression and gene functional annotation data. Second, it provides the visualization of condition-specific expression profiles. Third, it allows users to search co-regulated genes under the infections of various pathogens.

  • AraPPISite [by Shiping Yang]

    AraPPISite is an integrated database presenting fine-grained protein-protein interaction site annotations for Arabidopsis thaliana.

  • MAPanalyzer [by Yuan Zhou]

    MAPanalyzer is a microtubule-associated protein (MAP)-centered online  tool,  which includes a MAP database and a MAP predictor.The core dataset of the MAP database was fully manually curated from the literature. And the MAP predictor was established through the integration of machine learning classifiers and homology searching method.

  • BEAN 2.0 [by Xiaotian Lu]

    Bacterial Effector Analyzer 2.0(BEAN 2.0) is an integrative web resource for prediction, analysis and storing type-III effectors.

  • Ralstonia solanacearum is a plant pathogen which can infect an unusually wide range of hosts. This bacterium and its host Arabidopsis thaliana have become a model system for studying the molecular basis of plant-pathogen interactions. For any phytopathogenic, protein-protein interactions (PPIs) play very important roles in infecting hosts. PPIs between R. solancearum and A. thaliana were constructed by two bioinformatic methods, the interolog and domain-based methods. The predicted PPIs were compiled as a PPI network called PPIRA, which contains 3074 PPIs between R. solancearum and A. thaliana.

  • NCPI represents a platform mainly to provide predicted protein-protein interactions(PPIs) in model fungus Neurospora crassa. This database, which has an intuitive query interface allowing an easy access to all the features of proteins, was built up using open source technologies (LAMP) and will be freely available at http://protein.cau.edu.cn/ncpi. The predicted protein-protein interactions are obtained using two methods.

  • Protein-protein interaction interactions tend to be evolutionary conserved cross species. Therefore we can predict protein-protein interactions in Magnaporthe grisea using model organism protein interaction datasets. Based on this method, we have built a network of 11674 predicted physical interactions among 3017 M.grisea proteins.