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Data Mining Techniques for the Life Sciences

Volume 609 of the series Methods in Molecular Biology pp 129-144

Date:

Biomolecular Pathway Databases

  • Hong Sain OoiAffiliated withBioinformatics Institute (BII), Agency for science, Technology, and Research (A*STAR)
  • , Georg SchneiderAffiliated withBioinformatics Institute (BII), Agency for science, Technology, and Research (A*STAR)
  • , Teng-Ting LimAffiliated withBioinformatics Institute (BII), Agency for science, Technology, and Research (A*STAR)
  • , Ying-Leong ChanAffiliated withBioinformatics Institute (BII), Agency for science, Technology, and Research (A*STAR)
  • , Birgit EisenhaberAffiliated withExperimental Therapeutic Centre (ETC), Bioinformatics Institute (BII), Agency for science, Technology, and Research (A*STAR)
  • , Frank EisenhaberAffiliated withBioinformatics Institute (BII), Agency for science, Technology, and Research (A*STAR)

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Abstract

From the database point of view, biomolecular pathways are sets of proteins and other biomacromolecules that represent spatio-temporally organized cascades of interactions with the involvement of low-molecular compounds and are responsible for achieving specific phenotypic biological outcomes. A pathway is usually associated with certain subcellular compartments. In this chapter, we analyze the major public biomolecular pathway databases. Special attention is paid to database scope, completeness, issues of annotation reliability, and pathway classification. In addition, systems for information retrieval, tools for mapping user-defined gene sets onto the information in pathway databases, and their typical research applications are reviewed. Whereas today, pathway databases contain almost exclusively qualitative information, the desired trend is toward quantitative description of interactions and reactions in pathways, which will gradually enable predictive modeling and transform the pathway databases into analytical workbenches.

Key words

biomolecular pathway database pathway KEGG