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NAR Molecular Biology Database Collection entry number 748
Huang T.W.1,2, Tien A.C.1, Huang W.C.2, Lee Y.C.G.1,3, Peng C.L.2, Tseng H.H.1,2, Kao C.Y.2 and Huang C.Y. F.1,2,4
1Division of Molecular and Genomic Medicine, National Health Research Institutes, Taipei 115, Taiwan, Republic of China
2Department of Computer Science and Information Engineering, National Taiwan University, Taipei 106, Taiwan, Republic of China
3Graduate Institute of Medical Informatics, Taipei Medical University, Taipei 110, Taiwan, Republic of China
4Institute of Biotechnology in Medicine, National Yang-Ming University, Taipei 112, Taiwan, Republic of China

Database Description

One possible path towards understanding the biological function of a target protein is through the discovery of how it interfaces within protein-protein interaction networks. The goal of this study was to create a virtual protein-protein interaction model using the concepts of orthologous conservation (or interologs) to elucidate the interacting networks of a particular target protein. POINT (the prediction of interactome database) is a functional database for the prediction of the human protein-protein interactome based on available orthologous interactome datasets. POINT integrates several publicly accessible databases, with emphasis placed on the extraction of a large quantity of mouse, fruit fly, worm and yeast protein-protein interactions datasets from the Database of Interacting Proteins (DIP), followed by conversion of them into a predicted human interactome. In addition, protein-protein interactions require both temporal synchronicity and precise spatial proximity. POINT therefore also incorporates correlated mRNA expression clusters obtained from cell cycle microarray databases and subcellular localization from Gene Ontology to further pinpoint the likelihood of biological relevance of each predicted interacting sets of protein partners.


We would like to thank DIP, GO, NCBI, PIR-NREF, UniProt for their public accessible databases and software that provided the foundation for construction of this applied POINT database. Development of the POINT database was supported by grants from the National Science Council (NSC92-3112-B-400-005) and National Health Research Institutes to C. F. H

Go to the abstract in Bioinformatics, 2004, 20, 3273-3276
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