This article is part of the supplement: Proceedings of the 2009 International Conference on Bioinformatics & Computational Biology (BioComp 2009)
Global protein interactome exploration through mining genome-scale data in Arabidopsis thaliana
- Equal contributors
1 College of Life Sciences, the Northeast Forestry University, Harbin, Heilongjiang 150040, China
2 The Center for Bioinformatics and Computational Biology, and The Institute of Biomedical Sciences, School of Life Science, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China
3 Shanghai Information Center for Life Sciences, Chinese Academy of Sciences, Shanghai, China, 200031
4 Rush Cancer Center, Rush University Medical Center, Chicago, IL 60612, USA
5 Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, MS-39406, USA
6 Daqing Institute of Biotechnology, Northeast Forestry University, Daqing, Heilongjiang 163316, China
BMC Genomics 2010, 11(Suppl 2):S2 doi:10.1186/1471-2164-11-S2-S2Published: 2 November 2010
Many essential cellular processes, such as cellular metabolism, transport, cellular metabolism and most regulatory mechanisms, rely on physical interactions between proteins. Genome-wide protein interactome networks of yeast, human and several other animal organisms have already been established, but this kind of network reminds to be established in the field of plant.
We first predicted the protein protein interaction in Arabidopsis thaliana with methods, including ortholog, SSBP, gene fusion, gene neighbor, phylogenetic profile, coexpression, protein domain, and used Naïve Bayesian approach next to integrate the results of these methods and text mining data to build a genome-wide protein interactome network. Furthermore, we adopted the data of GO enrichment analysis, pathway, published literature to validate our network, the confirmation of our network shows the feasibility of using our network to predict protein function and other usage.
Our interactome is a comprehensive genome-wide network in the organism plant Arabidopsis thaliana, and provides a rich resource for researchers in related field to study the protein function, molecular interaction and potential mechanism under different conditions.