title: PathwayBooster: a tool to support the curation of metabolic pathways.
abstract: BACKGROUND
  Despite several recent advances in the automated generation of draft metabolic reconstructions, the manual curation of these networks to produce high quality genome-scale metabolic models remains a labour-intensive and challenging task.
  
  
  RESULTS
  We present PathwayBooster, an open-source software tool to support the manual comparison and curation of metabolic models. It combines gene annotations from GenBank files and other sources with information retrieved from the metabolic databases BRENDA and KEGG to produce a set of pathway diagrams and reports summarising the evidence for the presence of a reaction in a given organism's metabolic network. By comparing multiple sources of evidence within a common framework, PathwayBooster assists the curator in the identification of likely false positive (misannotated enzyme) and false negative (pathway hole) reactions. Reaction evidence may be taken from alternative annotations of the same genome and/or a set of closely related organisms.
  
  
  CONCLUSIONS
  By integrating and visualising evidence from multiple sources, PathwayBooster reduces the manual effort required in the curation of a metabolic model. The software is available online at http://www.theosysbio.bio.ic.ac.uk/resources/pathwaybooster/ .
authors.affiliation: Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, SW7 2AZ, UK. r.liberal@imperial.ac.uk.
authors.forename: Rodrigo
authors.initials: R
authors.lastname: Liberal
authors.affiliation: Department of Biology and Biochemistry, University of Bath, Claverton Down, Bath BA2, 7AY, UK. b.k.lisowska@bath.ac.uk.
authors.forename: Beata K
authors.initials: BK
authors.lastname: Lisowska
authors.affiliation: Department of Biology and Biochemistry, University of Bath, Claverton Down, Bath BA2, 7AY, UK. d.j.leak@bath.ac.uk.
authors.forename: David J
authors.initials: DJ
authors.lastname: Leak
authors.affiliation: Centre for Integrative Systems Biology and Bioinformatics, Department of Life Sciences, Imperial College London, London, SW7 2AZ, UK. j.pinney@imperial.ac.uk.
authors.forename: John W
authors.initials: JW
authors.lastname: Pinney
mesh_terms: D003545:Cysteine / Q000378:metabolism; D016208:Databases, Factual; D004798:Enzymes / Q000235:genetics; D016678:Genome; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008715:Methionine / Q000378:metabolism; D008954:Models, Biological; D058977:Molecular Sequence Annotation; D012984:Software
chemical_list: D004798:Enzymes; D008715:Methionine; D003545:Cysteine