PAIR: the predicted Arabidopsis interactome resource.
PAIR: the predicted Arabidopsis interactome resource.
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PAIR：预测的拟南芥互作组资源
DOI：
10.1093/nar/gkq938
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发表时间：
2011-01
影响因子：
14.9
通讯作者：
Chen X
中科院分区：
文献类型：
--
作者：
Lin M;Shen X;Chen X
拟南芥相互作用组预测数据库（PAIR，http：//www.cls.zju.edu.cn/pair/）包含了5990个实验报道的拟南芥分子相互作用和145，494个预测的相互作用，是目前最全面、可靠性最高的拟南芥相互作用组数据集。PAIR通过微调的支持向量机模型预测相互作用，该模型集成了相互作用的间接证据，例如基因共表达，结构域相互作用，共享GO注释，共定位，系统发育谱相似性和其他生物体中的同源相互作用（interlogs）。这些预测预计将覆盖整个拟南芥相互作用组的24%，其可靠性估计为44%。使用两个独立的示例数据集来严格验证预测精度。PAIR具有用户友好的查询界面，为两种蛋白质之间的关系提供丰富的注释。一个图形交互网络浏览器也被纳入了PAIR网络界面，以方便挖掘具体途径。
The predicted Arabidopsis interactome resource (PAIR, http://www.cls.zju.edu.cn/pair/), comprised of 5990 experimentally reported molecular interactions in Arabidopsis thaliana together with 145,494 predicted interactions, is currently the most comprehensive data set of the Arabidopsis interactome with high reliability. PAIR predicts interactions by a fine-tuned support vector machine model that integrates indirect evidences for interaction, such as gene co-expressions, domain interactions, shared GO annotations, co-localizations, phylogenetic profile similarities and homologous interactions in other organisms (interologs). These predictions were expected to cover 24% of the entire Arabidopsis interactome, and their reliability was estimated to be 44%. Two independent example data sets were used to rigorously validate the prediction accuracy. PAIR features a user-friendly query interface, providing rich annotation on the relationships between two proteins. A graphical interaction network browser has also been integrated into the PAIR web interface to facilitate mining of specific pathways.
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影响因子：
14.9
作者：
Heazlewood, Joshua L.;Verboom, Robert E.;Millar, A. Harvey
通讯作者：
Millar, A. Harvey
拟南芥信息资源（TAIR）：基因结构和功能注释。
影响因子：
14.9
作者：
Swarbreck, David;Wilks, Christopher;Lamesch, Philippe;Berardini, Tanya Z.;Garcia-Hernandez, Margarita;Foerster, Hartmut;Li, Donghui;Meyer, Tom;Muller, Robert;Ploetz, Larry;Radenbaugh, Amie;Singh, Shanker;Swing, Vanessa;Tissier, Christophe;Zhang, Peifen;Huala, Eva
通讯作者：
Huala, Eva
影响因子：
14.9
作者：
Cui, Jian;Li, Peng;Li, Guang;Xu, Feng;Zhao, Chen;Li, Yuhua;Yang, Zhongnan;Wang, Guang;Yu, Qingbo;Li, Yixue;Shi, Tieliu
通讯作者：
Shi, Tieliu
影响因子：
4.4
作者：
De Bodt S;Proost S;Vandepoele K;Rouzé P;Van de Peer Y
通讯作者：
Van de Peer Y
影响因子：
11.6
作者：
Lee, KiYoung;Thorneycroft, David;Ideker, Trey
通讯作者：
Ideker, Trey