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PAIR: the predicted Arabidopsis interactome resource.
Mingzhi Lin1, Xueling Shen, Xin Chen
1Department of Bioinformatics and Institute of Biochemistry, Zhejiang University, Hangzhou, PR China.
Nucleic Acids Research
|October 19, 2010
Summary
The Predicted Arabidopsis Interactome Resource (PAIR) offers a comprehensive dataset of Arabidopsis thaliana molecular interactions. This valuable tool aids researchers in exploring plant protein networks and pathways.
Area of Science:
- Plant molecular biology
- Bioinformatics
- Systems biology
Background:
- Understanding protein-protein interactions is crucial for deciphering plant biological processes.
- Existing Arabidopsis thaliana interactome data is fragmented, limiting comprehensive analysis.
Purpose of the Study:
- To develop and present the Predicted Arabidopsis Interactome Resource (PAIR), a comprehensive and reliable database of molecular interactions in Arabidopsis thaliana.
- To integrate diverse evidence types for accurate prediction of novel protein interactions.
Main Methods:
- Utilized a support vector machine model incorporating gene co-expressions, domain interactions, GO annotations, co-localizations, phylogenetic profiles, and interologs.
- Integrated 5,990 experimentally validated interactions with 145,494 predicted interactions.
- Validated prediction accuracy using two independent datasets.
Main Results:
- The PAIR resource contains 151,484 interactions (5,990 experimental, 145,494 predicted) for Arabidopsis thaliana.
- Predicted interactions are estimated to cover 24% of the total interactome with 44% reliability.
- PAIR provides a user-friendly interface with detailed protein relationship annotations and a network browser.
Conclusions:
- PAIR represents the most comprehensive and reliable dataset of the Arabidopsis interactome to date.
- The integrated prediction approach enhances the discovery of potential protein interactions.
- PAIR facilitates efficient exploration and mining of Arabidopsis protein interaction networks and pathways.
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