Kinetic modeling of metabolism: Present and future

Mohammad Mazharul Islam; Wheaton Lane Schroeder; Rajib Saha

doi:10.1016/j.coisb.2021.04.003

Kinetic modeling of metabolism: Present and future

Mohammad Mazharul Islam, Wheaton Lane Schroeder, Rajib Saha

Research output: Contribution to journal › Review article › peer-review

13 Scopus citations

Abstract

Kinetic models of metabolism are predictors of temporal metabolic behavior of living organisms that integrate multi-omics data sets with reaction network models to interpret reaction rates, kinetic parameters, and enzyme levels. Modern kinetic modeling and parametrization frameworks are powerful tools for describing prokaryotic and eukaryotic metabolic behavior and promises successful application in human health, agriculture, and biotechnology. While the scarcity of in vivo data, computational expense, and scalability issues provide significant challenges, these can be circumvented by leveraging novel in silico data generation, training modules, and concerted effort from various fields of expertise.

Original language	English (US)
Pages (from-to)	72-78
Number of pages	7
Journal	Current Opinion in Systems Biology
Volume	26
DOIs	https://doi.org/10.1016/j.coisb.2021.04.003
State	Published - Jun 2021

Keywords

Kinetic modeling
Metabolic model
Systems biology

ASJC Scopus subject areas

Modeling and Simulation
General Biochemistry, Genetics and Molecular Biology
Drug Discovery
Computer Science Applications
Applied Mathematics

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10.1016/j.coisb.2021.04.003

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title = "Kinetic modeling of metabolism: Present and future",

abstract = "Kinetic models of metabolism are predictors of temporal metabolic behavior of living organisms that integrate multi-omics data sets with reaction network models to interpret reaction rates, kinetic parameters, and enzyme levels. Modern kinetic modeling and parametrization frameworks are powerful tools for describing prokaryotic and eukaryotic metabolic behavior and promises successful application in human health, agriculture, and biotechnology. While the scarcity of in vivo data, computational expense, and scalability issues provide significant challenges, these can be circumvented by leveraging novel in silico data generation, training modules, and concerted effort from various fields of expertise.",

keywords = "Kinetic modeling, Metabolic model, Systems biology",

author = "Islam, {Mohammad Mazharul} and Schroeder, {Wheaton Lane} and Rajib Saha",

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language = "English (US)",

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T2 - Present and future

AU - Islam, Mohammad Mazharul

AU - Schroeder, Wheaton Lane

AU - Saha, Rajib

N1 - Funding Information: This work was supported by the NSF EPSCoR Center for Root and Rhizobiome Innovation Grant [ 25-1215-0139-025 , 2019] and Nebraska Collaboration Initiative Grant [ 21-1106-6008 , 2020]. Publisher Copyright: © 2021 Elsevier Ltd

PY - 2021/6

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N2 - Kinetic models of metabolism are predictors of temporal metabolic behavior of living organisms that integrate multi-omics data sets with reaction network models to interpret reaction rates, kinetic parameters, and enzyme levels. Modern kinetic modeling and parametrization frameworks are powerful tools for describing prokaryotic and eukaryotic metabolic behavior and promises successful application in human health, agriculture, and biotechnology. While the scarcity of in vivo data, computational expense, and scalability issues provide significant challenges, these can be circumvented by leveraging novel in silico data generation, training modules, and concerted effort from various fields of expertise.

AB - Kinetic models of metabolism are predictors of temporal metabolic behavior of living organisms that integrate multi-omics data sets with reaction network models to interpret reaction rates, kinetic parameters, and enzyme levels. Modern kinetic modeling and parametrization frameworks are powerful tools for describing prokaryotic and eukaryotic metabolic behavior and promises successful application in human health, agriculture, and biotechnology. While the scarcity of in vivo data, computational expense, and scalability issues provide significant challenges, these can be circumvented by leveraging novel in silico data generation, training modules, and concerted effort from various fields of expertise.

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Kinetic modeling of metabolism: Present and future

Abstract

Keywords

ASJC Scopus subject areas

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