merlin, an improved framework for the reconstruction of high-quality genome-scale metabolic models

Genome-scale metabolic models have been recognised as useful tools for better understanding living organisms metabolism. merlin (https://www.merlin-sysbio.org/) is an open-source and user-friendly resource that hastens the models reconstruction process, conjugating manual and automatic procedures, w...

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Detalhes bibliográficos
Autor principal: Capela, João (author)
Outros Autores: Lagoa, Davide Rafael Santos (author), Rodrigues, Rúben André Costa (author), Cunha, Emanuel Rodrigues (author), Cruz, Fernando (author), Barbosa, Ana (author), Bastos, J. (author), Lima, Diogo (author), Ferreira, Eugénio C. (author), Rocha, Miguel (author), Dias, Oscar (author)
Formato: article
Idioma:eng
Publicado em: 2022
Assuntos:
Texto completo:https://hdl.handle.net/1822/78600
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/78600
Descrição
Resumo:Genome-scale metabolic models have been recognised as useful tools for better understanding living organisms metabolism. merlin (https://www.merlin-sysbio.org/) is an open-source and user-friendly resource that hastens the models reconstruction process, conjugating manual and automatic procedures, while leveraging the user's expertise with a curation-oriented graphical interface. An updated and redesigned version of merlin is herein presented. Since 2015, several features have been implemented in merlin, along with deep changes in the software architecture, operational flow, and graphical interface. The current version (4.0) includes the implementation of novel algorithms and third-party tools for genome functional annotation, draft assembly, model refinement, and curation. Such updates increased the user base, resulting in multiple published works, including genome metabolic (re-)annotations and model reconstructions of multiple (lower and higher) eukaryotes and prokaryotes. merlin version 4.0 is the only tool able to perform template based and de novo draft reconstructions, while achieving competitive performance compared to state-of-the art tools both for well and less-studied organisms.