4.7 Review

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

Journal

PLANT CELL AND ENVIRONMENT
Volume 39, Issue 5, Pages 1049-1057

Publisher

WILEY
DOI: 10.1111/pce.12673

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

Categories

Funding

  1. Chinese Academy of Sciences
  2. Bill & Melinda Gates Foundation
  3. EU [289582, 245143]
  4. Designer Breeding by Molecular Modules [XDA08020301]
  5. National Center for Supercomputer Applications
  6. Max Planck Society
  7. Biotechnology and Biological Sciences Research Council [BB/M017605/1, BB/L026996/1] Funding Source: researchfish
  8. BBSRC [BB/L026996/1, BB/M017605/1] Funding Source: UKRI

Ask authors/readers for more resources

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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available