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  • TryanoCyc-NAR-2014-ePub

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TrypanoCyc: a community-led biochemical pathways database for Trypanosoma brucei

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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  • Sanu Shameer
  • Flora J. Logan-Klumpler
  • Florence Vinson
  • Ludovic Cottret
  • Benjamin Merlet
  • Fiona Achcar
  • Michael Boshart
  • Matthew Berriman
  • Rainer Breitling
  • Frédéric Bringaud
  • Peter Bütikofer
  • Amy M. Cattanach
  • Bridget Bannerman-Chukualim
  • Darren J. Creek
  • Kathryn Crouch
  • Harry P. de Koning
  • Hubert Denise
  • Charles Ebikeme
  • Alan H. Fairlamb
  • Michael A. J. Ferguson
  • Michael L. Ginger
  • Christiane Hertz-Fowler
  • Eduard J. Kerkhoven
  • Pascal Mäser
  • Paul A. M. Michels
  • Archana Nayak
  • David W. Nes
  • Derek P. Nolan
  • Christian Olsen
  • Fatima Silva-Franco
  • Terry K. Smith
  • Martin C. Taylor
  • Aloysius G. M. Tielens
  • Jaap J. van Hellemond
  • Isabel M. Vincent
  • Shane R. Wilkinson
  • Susan Wyllie
  • Fred R. Opperdoes
  • Michael P. Barrett
  • Fabien Jourdan
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<mark>Journal publication date</mark>28/01/2015
<mark>Journal</mark>Nucleic Acids Research
Issue numberD1
Volume43
Number of pages8
Pages (from-to)D637-D644
Publication StatusPublished
Early online date9/10/14
<mark>Original language</mark>English

Abstract

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 (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.

Bibliographic note

C The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com