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Author (up) Aite, M.; Chevallier, M.; Frioux, C.; Trottier, C.; Got, J.; Cortes, M.P.; Mendoza, S.N.; Carrier, G.; Dameron, O.; Guillaudeux, N.; Latorre, M.; Loira, N.; Markov, G.V.; Maass, A.; Siegel, A. pdf  doi
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  Title Traceability, reproducibility and wiki-exploration for “a-la-carte” reconstructions of genome-scale metabolic models Type Journal Article
  Year 2018 Publication Plos Computational Biology Abbreviated Journal PLoS Comput. Biol.  
  Volume 14 Issue 5 Pages 25 pp  
  Keywords  
  Abstract Genome-scale metabolic models have become the tool of choice for the global analysis of microorganism metabolism, and their reconstruction has attained high standards of quality and reliability. Improvements in this area have been accompanied by the development of some major platforms and databases, and an explosion of individual bioinformatics methods. Consequently, many recent model s result from “a la carte” pipelines, combining the use of platforms, individual tools and biological expertise to enhance the quality of the reconstruction. Although very useful, introducing heterogeneous tools, that hardly interact with each other, causes loss of traceability and reproducibility in the reconstruction process. This represents a real obstacle, especially when considering less studied species whose metabolic reconstruction can greatly benefit from the comparison to good quality models of related organisms. This work proposes an adaptable workspace, AuReMe, for sustainable reconstructions or improvements of genome-scale metabolic models involving personalized pipelines. At each step, relevant information related to the modifications brought to the model by a method is stored. This ensures that the process is reproducible and documented regardless of the combination of tools used. Additionally, the workspace establishes a way to browse metabolic models and their metadata through the automatic generation of ad-hoc local wikis dedicated to monitoring and facilitating the process of reconstruction. AuReMe supports exploration and semantic query based on RDF databases. We illustrate how this workspace allowed handling, in an integrated way, the metabolic reconstructions of non-model organisms such as an extremophile bacterium or eukaryote algae. Among relevant applications, the latter reconstruction led to putative evolutionary insights of a metabolic pathway.  
  Address [Aite, Meaziane; Chevallier, Marie; Frioux, Cleamence; Trottier, Camille; Got, Jeanne; Dameron, Olivier; Guillaudeux, Nicolas; Siegel, Anne] Univ Rennes, INRIA, CNRS, IRISA, Rennes, France, Email: anne.siegel@irisa.fr  
  Corporate Author Thesis  
  Publisher Public Library Science Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1553-7358 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000434012100025 Approved no  
  Call Number UAI @ eduardo.moreno @ Serial 879  
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