Abstract
The prediction of new protein–protein interactions is important due to many unknown functions of biological pathways. In addition, many protein–protein interaction databases contain different types of protein interactions, i.e., protein associations, physical protein associations and direct protein interactions. Moreover, discovering new crucial protein–protein interactions through biological experiments is still difficult. Therefore, there is increasing demand to discover not only protein associations but also direct protein interactions. Many studies have predicted protein–protein interactions by directly using biological features, such as Gene Ontology (GO) functions and domains of protein structure between two interacting proteins. In this article, we propose TransDomain, a new method of predicting potential protein–protein interactions by using a new strong transitive relationship between interacting protein domains. Our results demonstrate that TransDomain can effectively predict potential protein–protein interactions from existing identified protein interaction relationships. TransDomain achieved 90% precision rate and 91% accuracy in the prediction of all types of protein–protein interactions and outperformed the existing PPI prediction systems and simulated GO-based prediction methods.
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Tang, YT., Kao, HY. (2011). TransDomain: A Transitive Domain-Based Method in Protein–Protein Interaction Prediction. In: Chen, J., Wang, J., Zelikovsky, A. (eds) Bioinformatics Research and Applications. ISBRA 2011. Lecture Notes in Computer Science(), vol 6674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21260-4_24
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DOI: https://doi.org/10.1007/978-3-642-21260-4_24
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