Literature DB >> 30065105

Methods for automated genome-scale metabolic model reconstruction.

José P Faria1, Miguel Rocha2, Isabel Rocha2, Christopher S Henry3.   

Abstract

In the era of next-generation sequencing and ubiquitous assembly and binning of metagenomes, new putative genome sequences are being produced from isolate and microbiome samples at ever-increasing rates. Genome-scale metabolic models have enormous utility for supporting the analysis and predictive characterization of these genomes based on sequence data. As a result, tools for rapid automated reconstruction of metabolic models are becoming critically important for supporting the analysis of new genome sequences. Many tools and algorithms have now emerged to support rapid model reconstruction and analysis. Here, we are comparing and contrasting the capabilities and output of a variety of these tools, including ModelSEED, Raven Toolbox, PathwayTools, SuBliMinal Toolbox and merlin.
© 2018 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Entities:  

Keywords:  genome annotation; genome-scale metabolic model; metabolic network

Mesh:

Year:  2018        PMID: 30065105     DOI: 10.1042/BST20170246

Source DB:  PubMed          Journal:  Biochem Soc Trans        ISSN: 0300-5127            Impact factor:   5.407


  13 in total

1.  Taxonomic weighting improves the accuracy of a gap-filling algorithm for metabolic models.

Authors:  Wai Kit Ong; Peter E Midford; Peter D Karp
Journal:  Bioinformatics       Date:  2020-03-01       Impact factor: 6.937

2.  Consistency, Inconsistency, and Ambiguity of Metabolite Names in Biochemical Databases Used for Genome-Scale Metabolic Modelling.

Authors:  Nhung Pham; Ruben G A van Heck; Jesse C J van Dam; Peter J Schaap; Edoardo Saccenti; Maria Suarez-Diez
Journal:  Metabolites       Date:  2019-02-06

3.  Metabolic Modeling of Cystic Fibrosis Airway Communities Predicts Mechanisms of Pathogen Dominance.

Authors:  Michael A Henson; Giulia Orazi; Poonam Phalak; George A O'Toole
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Review 4.  Machine and deep learning meet genome-scale metabolic modeling.

Authors:  Guido Zampieri; Supreeta Vijayakumar; Elisabeth Yaneske; Claudio Angione
Journal:  PLoS Comput Biol       Date:  2019-07-11       Impact factor: 4.475

5.  A systematic assessment of current genome-scale metabolic reconstruction tools.

Authors:  Sebastián N Mendoza; Brett G Olivier; Douwe Molenaar; Bas Teusink
Journal:  Genome Biol       Date:  2019-08-07       Impact factor: 13.583

6.  HAMAP as SPARQL rules-A portable annotation pipeline for genomes and proteomes.

Authors:  Jerven Bolleman; Edouard de Castro; Delphine Baratin; Sebastien Gehant; Beatrice A Cuche; Andrea H Auchincloss; Elisabeth Coudert; Chantal Hulo; Patrick Masson; Ivo Pedruzzi; Catherine Rivoire; Ioannis Xenarios; Nicole Redaschi; Alan Bridge
Journal:  Gigascience       Date:  2020-02-01       Impact factor: 6.524

Review 7.  Addressing uncertainty in genome-scale metabolic model reconstruction and analysis.

Authors:  David B Bernstein; Snorre Sulheim; Eivind Almaas; Daniel Segrè
Journal:  Genome Biol       Date:  2021-02-18       Impact factor: 13.583

8.  Strategies for Enhancing in vitro Degradation of Linuron by Variovorax sp. Strain SRS 16 Under the Guidance of Metabolic Modeling.

Authors:  Kusum Dhakar; Raphy Zarecki; Daniella van Bommel; Nadav Knossow; Shlomit Medina; Basak Öztürk; Radi Aly; Hanan Eizenberg; Zeev Ronen; Shiri Freilich
Journal:  Front Bioeng Biotechnol       Date:  2021-04-15

9.  Atlas: Automatic modeling of regulation of bacterial gene expression and metabolism using rule-based languages.

Authors:  Rodrigo Santibáñez; Daniel Garrido; Alberto J M Martin
Journal:  Bioinformatics       Date:  2020-12-26       Impact factor: 6.937

10.  gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models.

Authors:  Johannes Zimmermann; Christoph Kaleta; Silvio Waschina
Journal:  Genome Biol       Date:  2021-03-10       Impact factor: 13.583

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