http://repositorio.unb.br/handle/10482/24910
Fichier | Description | Taille | Format | |
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ARTIGO_ProvenanceBioinformaticsWorkflows.pdf | 2,74 MB | Adobe PDF | Voir/Ouvrir |
Titre: | Provenance in bioinformatics workflows |
Auteur(s): | Paula, Renato de Holanda, Maristela Gomes, Luciana S. A. Lifschitz, Sergio Walter, Maria Emília Machado Telles |
Assunto:: | Banco de dados Biologia computacional Fluxo de trabalho |
Date de publication: | nov-2013 |
Editeur: | BioMed Central |
Référence bibliographique: | PAULA, Renato de et al. Provenance in bioinformatics workflows. BMC Bioinformatics, Londres, v. 14, p. 1-14, 2013. Disponível em: <https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-14-S11-S6>. Acesso em: 18 out. 2017. |
Abstract: | In this work, we used the PROV-DM model to manage data provenance in workflows of genome projects. This provenance model allows the storage of details of one workflow execution, e.g., raw and produced data and computational tools, their versions and parameters. Using this model, biologists can access details of one particular execution of a workflow, compare results produced by different executions, and plan new experiments more efficiently. In addition to this, a provenance simulator was created, which facilitates the inclusion of provenance data of one genome project workflow execution. Finally, we discuss one case study, which aims to identify genes involved in specific metabolic pathways of Bacillus cereus, as well as to compare this isolate with other phylogenetic related bacteria from the Bacillus group. B. cereus is an extremophilic bacteria, collectemd in warm water in the Midwestern Region of Brazil, its DNA samples having been sequenced with an NGS machine. |
Licença:: | © 2013 de Paula et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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 stated. Fonte: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-14-S11-S6. Acesso em: 18 out. 2017. |
Collection(s) : | Artigos publicados em periódicos e afins |
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