@article{748950,
  abstract     = {{Background: Large-scale identification of the interrelationships between different components of the cell, such as the interactions between proteins, has recently gained great interest. However, unraveling large-scale protein-protein interaction maps is laborious and expensive. Moreover, assessing the reliability of the interactions can be cumbersome.

Results: In this study, we have developed a computational method that exploits the existing knowledge on protein-protein interactions in diverse species through orthologous relations on the one hand, and functional association data on the other hand to predict and filter protein-protein interactions in Arabidopsis thaliana. A highly reliable set of protein-protein interactions is predicted through this integrative approach making use of existing protein-protein interaction data from yeast, human, C. elegans and D. melanogaster. Localization, biological process, and co-expression data are used as powerful indicators for protein-protein interactions. The functional repertoire of the identified interactome reveals interactions between proteins functioning in well-conserved as well as plant-specific biological processes. We observe that although common mechanisms (e.g. actin polymerization) and components (e.g. ARPs, actin-related proteins) exist between different lineages, they are active in specific processes such as growth, cancer metastasis and trichome development in yeast, human and Arabidopsis, respectively.

Conclusion: We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions. Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered. Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.}},
  author       = {{De Bodt, Stefanie and Proost, Sebastian and Vandepoele, Klaas and Rouzé, Pierre and Van de Peer, Yves}},
  issn         = {{1471-2164}},
  journal      = {{BMC Genomics}},
  keywords     = {{PROBE LEVEL DATA,MOLECULAR INTERACTION DATABASE,SACCHAROMYCES-CEREVISIAE,INTERACTION NETWORKS,INTERACTION MAP,PROBABILISTIC MODEL,EXPRESSION DATA,TARGET GENES,C-ELEGANS,SCALE DATA}},
  language     = {{eng}},
  number       = {{288}},
  pages        = {{1--15}},
  title        = {{Predicting protein-protein interactions in Arabidopsis thaliana through integration of orthology, gene ontology and co-expression}},
  url          = {{http://doi.org/10.1186/1471-2164-10-288}},
  volume       = {{10}},
  year         = {{2009}},
}

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