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Databases of Protein–Protein Interactions and Complexes

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Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 609))

Abstract

In the current understanding, translation of genomic sequences into proteins is the most important path for realization of genome information. In exercising their intended function, proteins work together through various forms of direct (physical) or indirect interaction mechanisms. For a variety of basic functions, many proteins form a large complex representing a molecular machine or a macromolecular super-structural building block. After several high-throughput techniques for detection of protein–protein interactions had matured, protein interaction data became available in a large scale and curated databases for protein–protein interactions (PPIs) are a new necessity for efficient research. Here, their scope, annotation quality, and retrieval tools are reviewed. In addition, attention is paid to portals that provide unified access to a variety of such databases with added annotation value.

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Authors and Affiliations

  1. Bioinformatics Institute (BII), Agency for science, Technology, and Research (A*STAR), Singapore, Singapore

    Hong Sain Ooi, Georg Schneider, Ying-Leong Chan, Teng-Ting Lim & Frank Eisenhaber

  2. Experimental Therapeutic Centre (ETC), Bioinformatics Institute (BII), Agency for science, Technology, and Research (A*STAR), Singapore, Singapore

    Birgit Eisenhaber

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  1. Hong Sain Ooi
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  2. Georg Schneider
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  4. Teng-Ting Lim
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  5. Birgit Eisenhaber
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  1. Max F. Perutz Laboratories GmbH, Universität Wien, Dr. Bohr-Gasse 9, Wien, 1030, Austria

    Oliviero Carugo

  2. Research (A*STAR), Agency for Science & Technology, Biopolis Street 30, Singapore, 138671, Singapore

    Frank Eisenhaber

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Ooi, H.S., Schneider, G., Chan, YL., Lim, TT., Eisenhaber, B., Eisenhaber, F. (2010). Databases of Protein–Protein Interactions and Complexes. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 609. Humana Press. https://doi.org/10.1007/978-1-60327-241-4_9

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  • DOI: https://doi.org/10.1007/978-1-60327-241-4_9

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