scholarly journals Applications of Genome-Scale Metabolic Models in Biotechnology and Systems Medicine

2016 ◽  
Vol 6 ◽  
Author(s):  
Cheng Zhang ◽  
Qiang Hua
Keyword(s):  
Systems Medicine ◽  
Metabolic Models ◽  
Genome Scale

scholarly journals Consistency, Inconsistency and Ambiguity of Metabolite Names in Biochemical Databases Used for Genome Scale Metabolic Modelling

2018 ◽  
Author(s):  
Nhung Pham ◽  
Ruben Van Heck ◽  
Jesse van Dam ◽  
Peter Schaap ◽  
Edoardo Saccenti ◽  
...  
Keyword(s):  
Systems Medicine ◽  
Biochemical Reactions ◽  
Metabolic Modelling ◽  
Research Areas ◽  
Limit Model ◽  
Metabolic Models ◽  
Genome Scale ◽  
Manual Verification

Genome scale metabolic models (GEMs) are manually curated repositories describing the metabolic capabilities of an organism. GEMs have been successfully used in different research areas, ranging from systems medicine to biotechnology. However, the different naming conventions (namespaces) of databases used to build GEMs limit model reusability and prevent the integration of existing models. This problem is known in the GEM community but its extent has not been analyzed in depth. In this study, we investigate the name ambiguity and the multiplicity of non-systematic identifiers and we highlight the (in)consistency in their use in eleven biochemical databases of biochemical reactions and the problems that arise when mapping between different namespaces and databases. We found that such inconsistencies can be as high as 83.1%, thus emphasizing the need for strategies to deal with these issues. Currently, manual verification of the mappings appears to be the only solution to remove inconsistencies when combining models. Finally, we discuss several possible approaches to facilitate (future) unambiguous mapping.

scholarly journals RMetD2: a tool for integration of relative transcriptomics data into Genome-scale metabolic models

2019 ◽  
Author(s):  
Cheng Zhang ◽  
Sunjae Lee ◽  
Gholamreza Bidkhori ◽  
Rui Benfeitas ◽  
Alen Lovric ◽  
...  
Keyword(s):  
Case Studies ◽  
State Of The Art ◽  
Differentially Expressed ◽  
Systems Medicine ◽  
Transcriptomics Data ◽  
Altered Metabolism ◽  
Metabolic Models ◽  
Genome Scale ◽  
Potential Use ◽  
Single Set

AbstractRelative Metabolic Differences version 2 (RMetD2) is a tool for integration of differentially expressed (DE) genes into genome-scale metabolic models (GEMs) for revealing the altered metabolism between two biological conditions. This method provides a robust evaluation of the metabolism by using flux ranges instead of a single set of flux distributions. RMetD2 classifies reactions into three different groups, namely up-regulated, down-regulated and unchanged, which enables systematic interpretation of the metabolic differences between two different conditions. We employed this method in three different case studies using mice and human datasets, and compared it with state-of-the-art methods used for studying condition-specific metabolic differences using GEMs. We observed that RMetD2 is capable of capturing experimentally-observed features that are missed by other methods, highlighting its potential use in biotechnology and systems medicine applications. RMetD2 is implemented in Matlab and it is available without any limitation at https://sourceforge.net/projects/rmetd.

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

Metabolites ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 28 ◽  
Author(s):  
Nhung Pham ◽  
Ruben van Heck ◽  
Jesse van Dam ◽  
Peter Schaap ◽  
Edoardo Saccenti ◽  
...  
Keyword(s):  
Systems Medicine ◽  
Biochemical Reactions ◽  
Metabolic Modelling ◽  
Research Areas ◽  
Limit Model ◽  
Metabolic Models ◽  
Genome Scale ◽  
Manual Verification

Genome-scale metabolic models (GEMs) are manually curated repositories describing the metabolic capabilities of an organism. GEMs have been successfully used in different research areas, ranging from systems medicine to biotechnology. However, the different naming conventions (namespaces) of databases used to build GEMs limit model reusability and prevent the integration of existing models. This problem is known in the GEM community, but its extent has not been analyzed in depth. In this study, we investigate the name ambiguity and the multiplicity of non-systematic identifiers and we highlight the (in)consistency in their use in 11 biochemical databases of biochemical reactions and the problems that arise when mapping between different namespaces and databases. We found that such inconsistencies can be as high as 83.1%, thus emphasizing the need for strategies to deal with these issues. Currently, manual verification of the mappings appears to be the only solution to remove inconsistencies when combining models. Finally, we discuss several possible approaches to facilitate (future) unambiguous mapping.

Critical assessment of genome-scale metabolic models of Arabidopsis thaliana

2022 ◽  
Author(s):  
Javad Zamani ◽  
Sayed-Amir Marashi ◽  
Tahmineh Lohrasebi ◽  
Mohammad-Ali Malboobi ◽  
Esmail Foroozan
Keyword(s):  
Arabidopsis Thaliana ◽  
Flux Balance Analysis ◽  
Critical Assessment ◽  
Flux Balance ◽  
Balance Analysis ◽  
Metabolic Models ◽  
Living Organisms ◽  
Genome Scale

Genome-scale metabolic models (GSMMs) have enabled researchers to perform systems-level studies of living organisms. As a constraint-based technique, flux balance analysis (FBA) aids computation of reaction fluxes and prediction of...

Model-guided identification of novel gene amplification targets for improving succinate production in Escherichia coli NZN111

2017 ◽  
Vol 9 (10) ◽  
pp. 830-835 ◽  
Author(s):  
Xingxing Jian ◽  
Ningchuan Li ◽  
Qian Chen ◽  
Qiang Hua
Keyword(s):  
Escherichia Coli ◽  
Metabolic Engineering ◽  
Gene Amplification ◽  
Metabolic Networks ◽  
Computational Analysis ◽  
Succinate Production ◽  
Novel Gene ◽  
Metabolic Models ◽  
Genome Scale

Reconstruction and application of genome-scale metabolic models (GEMs) have facilitated metabolic engineering by providing a platform on which systematic computational analysis of metabolic networks can be performed.

scholarly journals A metabolite-centric view on flux distributions in genome-scale metabolic models

2013 ◽  
Vol 7 (1) ◽  
pp. 33 ◽  
Author(s):  
S Riemer ◽  
René Rex ◽  
Dietmar Schomburg
Keyword(s):  
Metabolic Models ◽  
Genome Scale

scholarly journals More than just a gut feeling: constraint-based genome-scale metabolic models for predicting functions of human intestinal microbes

Microbiome ◽  
2017 ◽  
Vol 5 (1) ◽  
Author(s):  
Kees C. H. van der Ark ◽  
Ruben G. A. van Heck ◽  
Vitor A. P. Martins Dos Santos ◽  
Clara Belzer ◽  
Willem M. de Vos
Keyword(s):  
Intestinal Microbes ◽  
Metabolic Models ◽  
Genome Scale

Recent advances in reconstruction and applications of genome-scale metabolic models

2012 ◽  
Vol 23 (4) ◽  
pp. 617-623 ◽  
Author(s):  
Tae Yong Kim ◽  
Seung Bum Sohn ◽  
Yu Bin Kim ◽  
Won Jun Kim ◽  
Sang Yup Lee
Keyword(s):  
Recent Advances ◽  
Metabolic Models ◽  
Genome Scale
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