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Shameer, Sanu; Logan-Klumpler, Flora J.; Vinson, Florence; Cottret, Ludovic; Merlet, Benjamin; Achcar, Fiona; Boshart, Michael; Berriman, Matthew; Breitling, Rainer; Bringaud, Frédéric; Bütikofer, Peter; Cattanach, Amy M.; Bannerman-Chukualim, Bridget; Creek, Darren J.; Crouch, Kathryn; Koning, Harry P. de; Denise, Hubert; Ebikeme, Charles; Fairlamb, Alan H.; Ferguson, Michael A. J.; Ginger, Michael L.; Hertz-Fowler, Christiane; Kerkhoven, Eduard J.; Mäser, Pascal; Michels, Paul A. M.; Nayak, Archana; Nes, David W.; Nolan, Derek P.; Olsen, Christian; Silva-Franco, Fatima; Smith, Terry K.; Taylor, Martin C.; Tielens, Aloysius G. M.; Urbaniak, Michael D.; Hellemond, Jaap J. van; Vincent, Isabel M.; Wilkinson, Shane R.; Wyllie, Susan; Opperdoes, Fred R.; Barrett, Michael P. and Jourdan, Fabien (2015): TrypanoCyc: a community-led biochemical pathways database for Trypanosoma brucei. In: Nucleic Acids Research, Vol. 43, No. D1: D637-D644 [PDF, 3MB]

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The metabolic network of a cell represents the catabolic and anabolic reactions that interconvert small molecules (metabolites) through the activity of enzymes, transporters and non-catalyzed chemical reactions. Our understanding of individual metabolic networks is increasing as we learn more about the enzymes that are active in particular cells under particular conditions and as technologies advance to allow detailed measurements of the cellular metabolome. Metabolic network databases are of increasing importance in allowing us to contextualise data sets emerging from transcriptomic, proteomic and metabolomic experiments. Here we present a dynamic database, TrypanoCyc ( ext-link-type="uri" xlink:href="http://www.metexplore.fr/trypanocyc/" xlink:type="simple">http://www.metexplore.fr/trypanocyc/), which describes the generic and condition-specific metabolic network of Trypanosoma brucei, a parasitic protozoan responsible for human and animal African trypanosomiasis. In addition to enabling navigation through the BioCyc-based TrypanoCyc interface, we have also implemented a network-based representation of the information through MetExplore, yielding a novel environment in which to visualise the metabolism of this important parasite.

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