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dc.contributor.authorKarlsen, Emil
dc.contributor.authorSchulz, Christian
dc.contributor.authorAlmaas, Eivind
dc.date.accessioned2019-01-29T16:22:46Z
dc.date.available2019-01-29T16:22:46Z
dc.date.created2018-12-17T09:42:24Z
dc.date.issued2018
dc.identifier.citationBMC Bioinformatics. (2018), 19:467.nb_NO
dc.identifier.issn1471-2105
dc.identifier.urihttp://hdl.handle.net/11250/2582946
dc.description.abstractBackground Constraint-based modeling is a widely used and powerful methodology to assess the metabolic phenotypes and capabilities of an organism. The starting point and cornerstone of all such modeling is a genome-scale metabolic network reconstruction. The creation, further development, and application of such networks is a growing field of research thanks to a plethora of readily accessible computational tools. While the majority of studies are focused on single-species analyses, typically of a microbe, the computational study of communities of organisms is gaining attention. Similarly, reconstructions that are unified for a multi-cellular organism have gained in popularity. Consequently, the rapid generation of genome-scale metabolic reconstructed networks is crucial. While multiple web-based or stand-alone tools are available for automated network reconstruction, there is, however, currently no publicly available tool that allows the swift assembly of draft reconstructions of community metabolic networks and consolidated metabolic networks for a specified list of organisms. Results Here, we present AutoKEGGRec, an automated tool that creates first draft metabolic network reconstructions of single organisms, community reconstructions based on a list of organisms, and finally a consolidated reconstruction for a list of organisms or strains. AutoKEGGRec is developed in Matlab and works seamlessly with the COBRA Toolbox v3, and it is based on only using the KEGG database as external input. The generated first draft reconstructions are stored in SBML files and consist of all reactions for a KEGG organism ID and corresponding linked genes. This provides a comprehensive starting point for further refinement and curation using the host of COBRA toolbox functions or other preferred tools. Through the data structures created, the tool also facilitates a comparative analysis of metabolic content in any given number of organisms present in the KEGG database. Conclusion AutoKEGGRec provides a first step in a metabolic network reconstruction process, filling a gap for tools creating community and consolidated metabolic networks. Based only on KEGG data as external input, the generated reconstructions consist of data with a directly traceable foundation and pedigree. With AutoKEGGRec, this kind of modeling is made accessible to a wider part of the genome-scale metabolic analysis community.nb_NO
dc.language.isoengnb_NO
dc.publisherBMCnb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAutomated generation of genome-scale metabolic draft reconstructions based on KEGGnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.journalBMC Bioinformaticsnb_NO
dc.identifier.doi10.1186/s12859-018-2472-z
dc.identifier.cristin1643852
dc.relation.projectNorges forskningsråd: 269084nb_NO
dc.relation.projectNorges forskningsråd: 271585nb_NO
dc.description.localcode© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise statednb_NO
cristin.unitcode194,66,15,0
cristin.unitcode194,65,20,0
cristin.unitnameInstitutt for bioteknologi og matvitenskap
cristin.unitnameInstitutt for samfunnsmedisin og sykepleie
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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