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BIOINFORMATICS

Computational Identification of Potential Molecular Interactions in Arabidopsis^1,[C],[W]

Department of Bioinformatics, Zhejiang University, Hangzhou, People's Republic of China, 310058 (M.L., B.H., L.C., Y.F., X.C.); and State Key Laboratory of Plant Physiology and Biochemistry, Zhejiang University, Hangzhou, People's Republic of China, 310058 (P.S., P.W.)

Knowledge of the protein interaction network is useful to assist molecular mechanism studies. Several major repositories have been established to collect and organize reported protein interactions. Many interactions have been reported in several model organisms, yet a very limited number of plant interactions can thus far be found in these major databases. Computational identification of potential plant interactions, therefore, is desired to facilitate relevant research. In this work, we constructed a support vector machine model to predict potential Arabidopsis (Arabidopsis thaliana) protein interactions based on a variety of indirect evidence. In a 100-iteration bootstrap evaluation, the confidence of our predicted interactions was estimated to be 48.67%, and these interactions were expected to cover 29.02% of the entire interactome. The sensitivity of our model was validated with an independent evaluation data set consisting of newly reported interactions that did not overlap with the examples used in model training and testing. Results showed that our model successfully recognized 28.91% of the new interactions, similar to its expected sensitivity (29.02%). Applying this model to all possible Arabidopsis protein pairs resulted in 224,206 potential interactions, which is the largest and most accurate set of predicted Arabidopsis interactions at present. In order to facilitate the use of our results, we present the Predicted Arabidopsis Interactome Resource, with detailed annotations and more specific per interaction confidence measurements. This database and related documents are freely accessible at http://www.cls.zju.edu.cn/pair/.

² These authors contributed equally to the article.

The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Xin Chen (xinchen{at}zju.edu.cn).

^[C] Some figures in this article are displayed in color online but in black and white in the print edition.

^[W] The online version of this article contains Web-only data.

www.plantphysiol.org/cgi/doi/10.1104/pp.109.141317

^* Corresponding author; e-mail xinchen{at}zju.edu.cn.

Received May 11, 2009; accepted July 6, 2009; published July 10, 2009.