An approach to pathway reconstruction using whole genome metabolic models and sensitive sequence searching

Metabolic models have the potential to impact on genome annotation and on the interpretation of gene expression and other high throughput genome data. The genome of Streptomyces coelicolor genome has been sequenced and some 30% of the open reading frames (ORFs) lack any functional annotation. A rece...

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Main Authors: Saqi Mansoor, Dobson Richard Jb., Kraben Preben, Hodgson David A., Wild David L.
Format: Article
Language:English
Published: De Gruyter 2009-03-01
Series:Journal of Integrative Bioinformatics
Online Access:https://doi.org/10.2390/biecoll-jib-2009-107
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spelling doaj-fe85838447e44b09ba1083aaee24cfbb2021-09-06T19:40:55ZengDe GruyterJournal of Integrative Bioinformatics1613-45162009-03-016111410.2390/biecoll-jib-2009-107An approach to pathway reconstruction using whole genome metabolic models and sensitive sequence searchingSaqi Mansoor0Dobson Richard Jb.1Kraben Preben2Hodgson David A.3Wild David L.4Barts and The London School of Medicine, Queen Mary, University of London, United Kingdom of Great Britain and Northern IrelandBarts and The London School of Medicine, Queen Mary, University of London, United Kingdom of Great Britain and Northern IrelandDepartment of Biochemical Engineering, University College London, United Kingdom of Great Britain and Northern IrelandBiological Sciences, University of Warwick, United Kingdom of Great Britain and Northern IrelandCentre for Systems Biology, University of Warwick, United Kingdom of Great Britain and Northern IrelandMetabolic models have the potential to impact on genome annotation and on the interpretation of gene expression and other high throughput genome data. The genome of Streptomyces coelicolor genome has been sequenced and some 30% of the open reading frames (ORFs) lack any functional annotation. A recently constructed metabolic network model for S. coelicolor highlights biochemical functions which should exist to make the metabolic model complete and consistent. These include 205 reactions for which no ORF is associated. Here we combine protein functional predictions for the unannotated open reading frames in the genome with ‘missing but expected’ functions inferred from the metabolic model. The approach allows function predictions to be evaluated in the context of the biochemical pathway reconstruction, and feed back iteratively into the metabolic model. We describe the approach and discuss a few illustrative examples.https://doi.org/10.2390/biecoll-jib-2009-107
collection DOAJ
language English
format Article
sources DOAJ
author Saqi Mansoor
Dobson Richard Jb.
Kraben Preben
Hodgson David A.
Wild David L.
spellingShingle Saqi Mansoor
Dobson Richard Jb.
Kraben Preben
Hodgson David A.
Wild David L.
An approach to pathway reconstruction using whole genome metabolic models and sensitive sequence searching
Journal of Integrative Bioinformatics
author_facet Saqi Mansoor
Dobson Richard Jb.
Kraben Preben
Hodgson David A.
Wild David L.
author_sort Saqi Mansoor
title An approach to pathway reconstruction using whole genome metabolic models and sensitive sequence searching
title_short An approach to pathway reconstruction using whole genome metabolic models and sensitive sequence searching
title_full An approach to pathway reconstruction using whole genome metabolic models and sensitive sequence searching
title_fullStr An approach to pathway reconstruction using whole genome metabolic models and sensitive sequence searching
title_full_unstemmed An approach to pathway reconstruction using whole genome metabolic models and sensitive sequence searching
title_sort approach to pathway reconstruction using whole genome metabolic models and sensitive sequence searching
publisher De Gruyter
series Journal of Integrative Bioinformatics
issn 1613-4516
publishDate 2009-03-01
description Metabolic models have the potential to impact on genome annotation and on the interpretation of gene expression and other high throughput genome data. The genome of Streptomyces coelicolor genome has been sequenced and some 30% of the open reading frames (ORFs) lack any functional annotation. A recently constructed metabolic network model for S. coelicolor highlights biochemical functions which should exist to make the metabolic model complete and consistent. These include 205 reactions for which no ORF is associated. Here we combine protein functional predictions for the unannotated open reading frames in the genome with ‘missing but expected’ functions inferred from the metabolic model. The approach allows function predictions to be evaluated in the context of the biochemical pathway reconstruction, and feed back iteratively into the metabolic model. We describe the approach and discuss a few illustrative examples.
url https://doi.org/10.2390/biecoll-jib-2009-107
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