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Plants in silico: why, why now and what?an integrative platform for plant systems biology research

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Plants in silico : why, why now and what?an integrative platform for plant systems biology research. / Zhu, Xin-Guang; Lynch, Jonathan P.; LeBauer, David S.; Millar, Andrew J.; Stitt, Mark; Long, Stephen P.

In: Plant, Cell and Environment, Vol. 39, No. 5, 05.2016, p. 1049-1057.

Research output: Contribution to journalLiterature reviewpeer-review

Harvard

Zhu, X-G, Lynch, JP, LeBauer, DS, Millar, AJ, Stitt, M & Long, SP 2016, 'Plants in silico: why, why now and what?an integrative platform for plant systems biology research', Plant, Cell and Environment, vol. 39, no. 5, pp. 1049-1057. https://doi.org/10.1111/pce.12673

APA

Zhu, X-G., Lynch, J. P., LeBauer, D. S., Millar, A. J., Stitt, M., & Long, S. P. (2016). Plants in silico: why, why now and what?an integrative platform for plant systems biology research. Plant, Cell and Environment, 39(5), 1049-1057. https://doi.org/10.1111/pce.12673

Vancouver

Zhu X-G, Lynch JP, LeBauer DS, Millar AJ, Stitt M, Long SP. Plants in silico: why, why now and what?an integrative platform for plant systems biology research. Plant, Cell and Environment. 2016 May;39(5):1049-1057. https://doi.org/10.1111/pce.12673

Author

Zhu, Xin-Guang ; Lynch, Jonathan P. ; LeBauer, David S. ; Millar, Andrew J. ; Stitt, Mark ; Long, Stephen P. / Plants in silico : why, why now and what?an integrative platform for plant systems biology research. In: Plant, Cell and Environment. 2016 ; Vol. 39, No. 5. pp. 1049-1057.

Bibtex

@article{182358fad88d4355b319826b7265cafa,
title = "Plants in silico: why, why now and what?an integrative platform for plant systems biology research",
abstract = "A paradigm shift is needed and timely in moving plant modelling from largely isolated efforts to a connected community endeavour that can take full advantage of advances in computer science and in mechanistic understanding of plant processes. Plants in silico (Psi) envisions a digital representation of layered dynamic modules, linking from gene networks and metabolic pathways through to cellular organization, tissue, organ and whole plant development, together with resource capture and use efficiency in dynamic competitive environments, ultimately allowing a mechanistically rich simulation of the plant or of a community of plants in silico. The concept is to integrate models or modules from different layers of organization spanning from genome to phenome to ecosystem in a modular framework allowing the use of modules of varying mechanistic detail representing the same biological process. Developments in high-performance computing, functional knowledge of plants, the internet and open-source version controlled software make achieving the concept realistic. Open source will enhance collaboration and move towards testing and consensus on quantitative theoretical frameworks. Importantly, Psi provides a quantitative knowledge framework where the implications of a discovery at one level, for example, single gene function or developmental response, can be examined at the whole plant or even crop and natural ecosystem levels.",
keywords = "plant models, crop models, ecosystem models, Earth System models, system analysis, virtual organisms, root architecture, photosynthesis, stomata, plant molecular biology, gene networks, metabolic networks, CANOPY PHOTOSYNTHESIS, THEORETICAL-ANALYSIS, CARBON METABOLISM, NEXT-GENERATION, ROOT SYSTEMS, WIDE-RANGE, WATER-USE, MODELS, CO2, ARABIDOPSIS",
author = "Xin-Guang Zhu and Lynch, {Jonathan P.} and LeBauer, {David S.} and Millar, {Andrew J.} and Mark Stitt and Long, {Stephen P.}",
year = "2016",
month = may,
doi = "10.1111/pce.12673",
language = "English",
volume = "39",
pages = "1049--1057",
journal = "Plant, Cell and Environment",
issn = "0140-7791",
publisher = "Wiley",
number = "5",

}

RIS

TY - JOUR

T1 - Plants in silico

T2 - why, why now and what?an integrative platform for plant systems biology research

AU - Zhu, Xin-Guang

AU - Lynch, Jonathan P.

AU - LeBauer, David S.

AU - Millar, Andrew J.

AU - Stitt, Mark

AU - Long, Stephen P.

PY - 2016/5

Y1 - 2016/5

N2 - A paradigm shift is needed and timely in moving plant modelling from largely isolated efforts to a connected community endeavour that can take full advantage of advances in computer science and in mechanistic understanding of plant processes. Plants in silico (Psi) envisions a digital representation of layered dynamic modules, linking from gene networks and metabolic pathways through to cellular organization, tissue, organ and whole plant development, together with resource capture and use efficiency in dynamic competitive environments, ultimately allowing a mechanistically rich simulation of the plant or of a community of plants in silico. The concept is to integrate models or modules from different layers of organization spanning from genome to phenome to ecosystem in a modular framework allowing the use of modules of varying mechanistic detail representing the same biological process. Developments in high-performance computing, functional knowledge of plants, the internet and open-source version controlled software make achieving the concept realistic. Open source will enhance collaboration and move towards testing and consensus on quantitative theoretical frameworks. Importantly, Psi provides a quantitative knowledge framework where the implications of a discovery at one level, for example, single gene function or developmental response, can be examined at the whole plant or even crop and natural ecosystem levels.

AB - A paradigm shift is needed and timely in moving plant modelling from largely isolated efforts to a connected community endeavour that can take full advantage of advances in computer science and in mechanistic understanding of plant processes. Plants in silico (Psi) envisions a digital representation of layered dynamic modules, linking from gene networks and metabolic pathways through to cellular organization, tissue, organ and whole plant development, together with resource capture and use efficiency in dynamic competitive environments, ultimately allowing a mechanistically rich simulation of the plant or of a community of plants in silico. The concept is to integrate models or modules from different layers of organization spanning from genome to phenome to ecosystem in a modular framework allowing the use of modules of varying mechanistic detail representing the same biological process. Developments in high-performance computing, functional knowledge of plants, the internet and open-source version controlled software make achieving the concept realistic. Open source will enhance collaboration and move towards testing and consensus on quantitative theoretical frameworks. Importantly, Psi provides a quantitative knowledge framework where the implications of a discovery at one level, for example, single gene function or developmental response, can be examined at the whole plant or even crop and natural ecosystem levels.

KW - plant models

KW - crop models

KW - ecosystem models

KW - Earth System models

KW - system analysis

KW - virtual organisms

KW - root architecture

KW - photosynthesis

KW - stomata

KW - plant molecular biology

KW - gene networks

KW - metabolic networks

KW - CANOPY PHOTOSYNTHESIS

KW - THEORETICAL-ANALYSIS

KW - CARBON METABOLISM

KW - NEXT-GENERATION

KW - ROOT SYSTEMS

KW - WIDE-RANGE

KW - WATER-USE

KW - MODELS

KW - CO2

KW - ARABIDOPSIS

U2 - 10.1111/pce.12673

DO - 10.1111/pce.12673

M3 - Literature review

VL - 39

SP - 1049

EP - 1057

JO - Plant, Cell and Environment

JF - Plant, Cell and Environment

SN - 0140-7791

IS - 5

ER -