4.5 Article

ArthropodaCyc: a CycADS powered collection of BioCyc databases to analyse and compare metabolism of arthropods

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OXFORD UNIV PRESS
DOI: 10.1093/database/baw081

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资金

  1. ANR Blanc Program IMetSym [ANR-13-BSV7-0016-03]
  2. Spanish Ministry of Economy and Competitiveness
  3. Centro de Excelencia Severo Ochoa - European Regional Development Fund (ERDF) [SEV-2012-0208, BIO2012-37161]
  4. Agence Nationale de la Recherche (ANR) [ANR-13-BSV7-0016] Funding Source: Agence Nationale de la Recherche (ANR)
  5. ICREA Funding Source: Custom

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Arthropods interact with humans at different levels with highly beneficial roles (e.g. as pollinators), as well as with a negative impact for example as vectors of human or animal diseases, or as agricultural pests. Several arthropod genomes are available at present and many others will be sequenced in the near future in the context of the i5K initiative, offering opportunities for reconstructing, modelling and comparing their metabolic networks. In-depth analysis of these genomic data through metabolism reconstruction is expected to contribute to a better understanding of the biology of arthropods, thereby allowing the development of new strategies to control harmful species. In this context, we present here ArthropodaCyc, a dedicated BioCyc collection of databases using the Cyc annotation database system (CycADS), allowing researchers to perform reliable metabolism comparisons of fully sequenced arthropods genomes. Since the annotation quality is a key factor when performing such global genome comparisons, all proteins from the genomes included in the ArthropodaCyc database were re-annotated using several annotation tools and orthology information. All functional/domain annotation results and their sources were integrated in the databases for user access. Currently, ArthropodaCyc offers a centralized repository of metabolic pathways, protein sequence domains, Gene Ontology annotations as well as evolutionary information for 28 arthropod species. Such database collection allows metabolism analysis both with integrated tools and through extraction of data in formats suitable for systems biology studies.

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