Depicts and integrates the information pertaining to protein-protein interaction networks, domain architecture, ortholog information and GO annotation in the Arabidopsis thaliana proteome. AtPID predicts the Protein-protein interaction pairs by integrating several methods with the Naive Baysian Classifier. All other related information curated in the AtPID is manually extracted from published literatures and other resources from some expert biologists. AtPID collects 5564 mutants with significant morphological alterations which were manually curated to 167 plant ontology (PO) morphology categories and predicts 4457 high confidence gene-PO pairs with 1369 genes as the complement. These single/multiple-gene mutants are indexed and linked to 3919 genes.

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AtPID classification

  • Plants
    • Arabidopsis thaliana

AtPID specifications

Restrictions to use:
Academic users only
Community driven:
No
User data submission:
Allowed
Programming languages:
Javascript
Data access:
File download, Web user interface
Version:
5.0

Publications

  • (Lv et al., 2016) AtPID: a genome-scale resource for genotype–phenotype associations in Arabidopsis. Nucleic Acids Res.
    DOI: 10.1093/nar/gkw1029
  • (Li et al., 2011) AtPID: the overall hierarchical functional protein interaction network interface and analytic platform for Arabidopsis. Nucleic acids research.
    PMID: 21036873
  • (Cui et al., 2008) AtPID: Arabidopsis thaliana protein interactome database--an integrative platform for plant systems biology. Nucleic Acids Res.
    PMID: 17962307
  • (Lv et al., 2016) AtPID: a genome-scale resource for genotype–phenotype associations in Arabidopsis. Nucleic Acids Research.
    PMID: 27899679

AtPID support

Documentation

Maintainer

Credits

Institution(s)

Center for Bioinformatics and Computational Biology, and the Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, China; School of Finance and Statistics, East China Normal University, Shanghai, China

Funding source(s)

National Key Basic Research and Development Plan 973 (2013CB127005), National High Technology Research and Development Program of China (2015AA020108), National Science Foundation of China (31171264, 31401133, 31671377), 111 Project (B14019), Science and Technology Commission of Shanghai Municipality (14YF1404400), Ernst Mach-Stipendien Eurasia-Pacific Uninet programme, China Postdoctoral Science Foundation funded project and the Supercomputer Center of East China Normal University.

Link to literature

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