Opportunities at the interface of network science and metabolic modeling

Varshit Dusad; Denise Thiel; Mauricio Barahona; Hector C. Keun; Diego A. Oyarzún

doi:10.3389/fbioe.2020.591049

Opportunities at the interface of network science and metabolic modeling

Varshit Dusad, Denise Thiel, Mauricio Barahona, Hector C. Keun, Diego A. Oyarzún^*

^*Corresponding author for this work

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

Abstract / Description of output

Metabolism plays a central role in cell physiology because it provides the molecular machinery for growth. At the genome-scale, metabolism is made up of thousands of reactions interacting with one another. Untangling this complexity is key to understand how cells respond to genetic, environmental, or therapeutic perturbations. Here we discuss the roles of two complementary strategies for the analysis of genome-scale metabolic models: Flux Balance Analysis (FBA) and network science. While FBA estimates metabolic flux on the basis of an optimization principle, network approaches reveal emergent properties of the global metabolic connectivity. We highlight how the integration of both approaches promises to deliver insights on the structure and function of metabolic systems with wide-ranging implications in discovery science, precision medicine and industrial biotechnology.

Original language	English
Article number	591049
Number of pages	9
Journal	Frontiers in Bioengineering and Biotechnology
Volume	8
DOIs	https://doi.org/10.3389/fbioe.2020.591049
Publication status	Published - 25 Jan 2021

Keywords / Materials (for Non-textual outputs)

flux balance analysis
genome scale metabolic modeling
machine learning
network science
synthetic biology
systems biology

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10.3389/fbioe.2020.591049Licence: Creative Commons: Attribution (CC-BY)

OyarzúnEtalFBB2021OpportunitiesATheInterfaceOfNetworkScienceFinal published version, 486 KBLicence: Creative Commons: Attribution (CC-BY)

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@article{458934ffbaf94eda988389421162e80e,

title = "Opportunities at the interface of network science and metabolic modeling",

abstract = "Metabolism plays a central role in cell physiology because it provides the molecular machinery for growth. At the genome-scale, metabolism is made up of thousands of reactions interacting with one another. Untangling this complexity is key to understand how cells respond to genetic, environmental, or therapeutic perturbations. Here we discuss the roles of two complementary strategies for the analysis of genome-scale metabolic models: Flux Balance Analysis (FBA) and network science. While FBA estimates metabolic flux on the basis of an optimization principle, network approaches reveal emergent properties of the global metabolic connectivity. We highlight how the integration of both approaches promises to deliver insights on the structure and function of metabolic systems with wide-ranging implications in discovery science, precision medicine and industrial biotechnology.",

keywords = "flux balance analysis, genome scale metabolic modeling, machine learning, network science, synthetic biology, systems biology",

author = "Varshit Dusad and Denise Thiel and Mauricio Barahona and Keun, {Hector C.} and Oyarz{\'u}n, {Diego A.}",

note = "Funding Information: This work was supported by Cancer Research UK (C24523/A27435), the Cancer Research UK Imperial Centre, and the EPSRC Centre for Mathematics of Precision Healthcare (EP/N014529/1). Publisher Copyright: {\textcopyright} Copyright {\textcopyright} 2021 Dusad, Thiel, Barahona, Keun and Oyarz{\'u}n.",

year = "2021",

month = jan,

day = "25",

doi = "10.3389/fbioe.2020.591049",

language = "English",

volume = "8",

journal = "Frontiers in Bioengineering and Biotechnology",

issn = "2296-4185",

publisher = "Frontiers Research Foundation",

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TY - JOUR

T1 - Opportunities at the interface of network science and metabolic modeling

AU - Dusad, Varshit

AU - Thiel, Denise

AU - Barahona, Mauricio

AU - Keun, Hector C.

AU - Oyarzún, Diego A.

N1 - Funding Information: This work was supported by Cancer Research UK (C24523/A27435), the Cancer Research UK Imperial Centre, and the EPSRC Centre for Mathematics of Precision Healthcare (EP/N014529/1). Publisher Copyright: © Copyright © 2021 Dusad, Thiel, Barahona, Keun and Oyarzún.

PY - 2021/1/25

Y1 - 2021/1/25

N2 - Metabolism plays a central role in cell physiology because it provides the molecular machinery for growth. At the genome-scale, metabolism is made up of thousands of reactions interacting with one another. Untangling this complexity is key to understand how cells respond to genetic, environmental, or therapeutic perturbations. Here we discuss the roles of two complementary strategies for the analysis of genome-scale metabolic models: Flux Balance Analysis (FBA) and network science. While FBA estimates metabolic flux on the basis of an optimization principle, network approaches reveal emergent properties of the global metabolic connectivity. We highlight how the integration of both approaches promises to deliver insights on the structure and function of metabolic systems with wide-ranging implications in discovery science, precision medicine and industrial biotechnology.

AB - Metabolism plays a central role in cell physiology because it provides the molecular machinery for growth. At the genome-scale, metabolism is made up of thousands of reactions interacting with one another. Untangling this complexity is key to understand how cells respond to genetic, environmental, or therapeutic perturbations. Here we discuss the roles of two complementary strategies for the analysis of genome-scale metabolic models: Flux Balance Analysis (FBA) and network science. While FBA estimates metabolic flux on the basis of an optimization principle, network approaches reveal emergent properties of the global metabolic connectivity. We highlight how the integration of both approaches promises to deliver insights on the structure and function of metabolic systems with wide-ranging implications in discovery science, precision medicine and industrial biotechnology.

KW - flux balance analysis

KW - genome scale metabolic modeling

KW - machine learning

KW - network science

KW - synthetic biology

KW - systems biology

U2 - 10.3389/fbioe.2020.591049

DO - 10.3389/fbioe.2020.591049

M3 - Review article

AN - SCOPUS:85100676796

SN - 2296-4185

VL - 8

JO - Frontiers in Bioengineering and Biotechnology

JF - Frontiers in Bioengineering and Biotechnology

M1 - 591049

ER -

Opportunities at the interface of network science and metabolic modeling

Abstract / Description of output

Keywords / Materials (for Non-textual outputs)

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