Metabolic kinetic modeling provides insight into complex biological questions, but hurdles remain
Abstract
Metabolic models containing kinetic information can answer unique questions about cellular metabolism that are useful to metabolic engineering. Several kinetic modeling frameworks have recently been developed or improved. In addition, techniques for systematic identification of model structure, including regulatory interactions, have been reported. Each framework has advantages and limitations, which can make it difficult to choose the most appropriate framework. Common limitations are data availability and computational time, especially in large-scale modeling efforts. However, recently developed experimental techniques, parameter identification algorithms, as well as model reduction techniques help alleviate these computational bottlenecks. Opportunities for additional improvements may come from the rich literature in catalysis and chemical networks. In all, kinetic models are positioned to make significant impact in cellular engineering.
- Authors:
-
- Northwestern Univ., Evanston, IL (United States)
- Publication Date:
- Research Org.:
- Dow Chemical Co., Midland, MI (United States); Northwestern Univ., Evanston, IL (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- OSTI Identifier:
- 1799347
- Alternate Identifier(s):
- OSTI ID: 1567956
- Grant/Contract Number:
- EE0007728; SC0018249; T32-GM008449-23; DEEE0007728; DESC0018249; MCB-1614953; DGE-1324585
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Current Opinion in Biotechnology
- Additional Journal Information:
- Journal Volume: 59; Journal Issue: C; Journal ID: ISSN 0958-1669
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; Biochemistry & Molecular Biology; Biotechnology & Applied Microbiology
Citation Formats
Strutz, Jonathan, Martin, Jacob, Greene, Jennifer, Broadbelt, Linda, and Tyo, Keith. Metabolic kinetic modeling provides insight into complex biological questions, but hurdles remain. United States: N. p., 2019.
Web. doi:10.1016/j.copbio.2019.02.005.
Strutz, Jonathan, Martin, Jacob, Greene, Jennifer, Broadbelt, Linda, & Tyo, Keith. Metabolic kinetic modeling provides insight into complex biological questions, but hurdles remain. United States. https://doi.org/10.1016/j.copbio.2019.02.005
Strutz, Jonathan, Martin, Jacob, Greene, Jennifer, Broadbelt, Linda, and Tyo, Keith. Thu .
"Metabolic kinetic modeling provides insight into complex biological questions, but hurdles remain". United States. https://doi.org/10.1016/j.copbio.2019.02.005. https://www.osti.gov/servlets/purl/1799347.
@article{osti_1799347,
title = {Metabolic kinetic modeling provides insight into complex biological questions, but hurdles remain},
author = {Strutz, Jonathan and Martin, Jacob and Greene, Jennifer and Broadbelt, Linda and Tyo, Keith},
abstractNote = {Metabolic models containing kinetic information can answer unique questions about cellular metabolism that are useful to metabolic engineering. Several kinetic modeling frameworks have recently been developed or improved. In addition, techniques for systematic identification of model structure, including regulatory interactions, have been reported. Each framework has advantages and limitations, which can make it difficult to choose the most appropriate framework. Common limitations are data availability and computational time, especially in large-scale modeling efforts. However, recently developed experimental techniques, parameter identification algorithms, as well as model reduction techniques help alleviate these computational bottlenecks. Opportunities for additional improvements may come from the rich literature in catalysis and chemical networks. In all, kinetic models are positioned to make significant impact in cellular engineering.},
doi = {10.1016/j.copbio.2019.02.005},
journal = {Current Opinion in Biotechnology},
number = C,
volume = 59,
place = {United States},
year = {Thu Mar 07 00:00:00 EST 2019},
month = {Thu Mar 07 00:00:00 EST 2019}
}
Web of Science
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