Abstract

A recent initiative named 'Crops in silico' proposes that multi-scale models “have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts” in plant science, particularly directed to crop species. To that end, the group called for “a paradigm shift in plant modelling, from largely isolated efforts to a connected community” (Marshall-Colon et al., 2017). ‘Wet’ (experimental) research has been especially productive in plant science, since the adoption of Arabidopsis thaliana as a laboratory model species allowed the emergence of an Arabidopsis research community. Parts of this community invested in ‘dry’ (theoretical) research, under the rubric of Systems Biology. Our past research combined concepts from systems biology and crop modelling (Chew et al., 2017; Chew et al., 2014b). Here we outline the approaches that seem most relevant to connected, ‘digital organism’ initiatives. We illustrate the scale of experimental research required, by collecting the kinetic parameter values that are required for a quantitative, dynamic model of a gene regulatory network. By comparison to the SBML community, we note computational resources and community structures that will help to realise the potential for plant systems biology to connect with a broader crop science community.
Original languageEnglish
Article numberJEXBOT/2018/235879
Pages (from-to) 2403–2418
Number of pages16
JournalJournal of Experimental Botany
Volume70
Issue number9
Early online date5 Jan 2019
DOIs
Publication statusPublished - 15 Apr 2019

Keywords

  • Arabidopsis thaliana
  • biochemical kinetics
  • community standards
  • computational modelling
  • data science
  • whole cell modelling

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