Literature DB >> 26079294

Genome scale models of yeast: towards standardized evaluation and consistent omic integration.

Benjamín J Sánchez1, Jens Nielsen.   

Abstract

Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published and are currently used for metabolic engineering and elucidating biological interactions. Here we review the history of yeast's GEMs, focusing on recent developments. We study how these models are typically evaluated, using both descriptive and predictive metrics. Additionally, we analyze the different ways in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted.

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Year:  2015        PMID: 26079294     DOI: 10.1039/c5ib00083a

Source DB:  PubMed          Journal:  Integr Biol (Camb)        ISSN: 1757-9694            Impact factor:   2.192


  15 in total

Review 1.  Metabolic network modeling with model organisms.

Authors:  L Safak Yilmaz; Albertha Jm Walhout
Journal:  Curr Opin Chem Biol       Date:  2017-01-12       Impact factor: 8.822

2.  Exposure to the lampricide TFM elicits an environmental stress response in yeast.

Authors:  Karen L Hinkle; Darlene Olsen
Journal:  FEMS Yeast Res       Date:  2019-01-01       Impact factor: 2.796

3.  Comparative Analysis of Yeast Metabolic Network Models Highlights Progress, Opportunities for Metabolic Reconstruction.

Authors:  Benjamin D Heavner; Nathan D Price
Journal:  PLoS Comput Biol       Date:  2015-11-13       Impact factor: 4.475

4.  Using Gene Essentiality and Synthetic Lethality Information to Correct Yeast and CHO Cell Genome-Scale Models.

Authors:  Ratul Chowdhury; Anupam Chowdhury; Costas D Maranas
Journal:  Metabolites       Date:  2015-09-29

5.  Improving the flux distributions simulated with genome-scale metabolic models of Saccharomyces cerevisiae.

Authors:  Rui Pereira; Jens Nielsen; Isabel Rocha
Journal:  Metab Eng Commun       Date:  2016-05-13

6.  Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints.

Authors:  Benjamín J Sánchez; Cheng Zhang; Avlant Nilsson; Petri-Jaan Lahtvee; Eduard J Kerkhoven; Jens Nielsen
Journal:  Mol Syst Biol       Date:  2017-08-03       Impact factor: 11.429

7.  Gsmodutils: a python based framework for test-driven genome scale metabolic model development.

Authors:  James Gilbert; Nicole Pearcy; Rupert Norman; Thomas Millat; Klaus Winzer; John King; Charlie Hodgman; Nigel Minton; Jamie Twycross
Journal:  Bioinformatics       Date:  2019-09-15       Impact factor: 6.937

8.  Integration of enzyme constraints in a genome-scale metabolic model of Aspergillus niger improves phenotype predictions.

Authors:  Jingru Zhou; Yingping Zhuang; Jianye Xia
Journal:  Microb Cell Fact       Date:  2021-06-30       Impact factor: 5.328

Review 9.  Genome-scale modeling of yeast: chronology, applications and critical perspectives.

Authors:  Helder Lopes; Isabel Rocha
Journal:  FEMS Yeast Res       Date:  2017-08-01       Impact factor: 2.796

10.  Elucidating redox balance shift in Scheffersomyces stipitis' fermentative metabolism using a modified genome-scale metabolic model.

Authors:  Matthew Hilliard; Andrew Damiani; Q Peter He; Thomas Jeffries; Jin Wang
Journal:  Microb Cell Fact       Date:  2018-09-05       Impact factor: 5.328

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