Author
MARSHALL-COLON, AMY - University Of Illinois | |
LONG, STEPHEN - University Of Illinois | |
Allen, Douglas - Doug | |
ALLEN, GABRIELLE - University Of Illinois | |
BEARD, DANIEL - University Of Michigan | |
BENES, BEDRICH - Purdue University | |
CAEMMERER, SUSANNE VON - Australian National University | |
CHRISTENSEN, AJ - University Of Illinois | |
COX, DONNA - University Of Illinois | |
HART, JOHN - University Of Illinois | |
HIRST, PETER - Purdue University | |
KANNAN, KAVYA - University Of Illinois | |
KATZ, DANIEL - University Of Illinois | |
LYNCH, JONATHAN - Pennsylvania State University | |
MILLAR, ANDREW - University Of Edinburgh | |
PANNEERSELVAN, BALAJI - University Of Illinois | |
PRICE, NATHAN - Institute For Systems Biology | |
PRUSINKIEWICZ, PRZEMYSLAW - University Of Calgary | |
RAILA, DAVID - University Of Illinois | |
SHEKAR, RACHEL - University Of Illinois | |
SHRIVASTAVA, STUTI - University Of Illinois | |
SHUKLA, DIWAKAR - University Of Illinois | |
SRINIVASAN, VENKATRAMAN - University Of Illinois | |
STITT, MARK - Max Planck Institute Of Molecular Plant Physiology | |
TURK, MATTHEW - University Of Illinois | |
VOIT, EBERHARD - Georgia Tech | |
WANG, YU - University Of Illinois | |
YIN, XINYOU - Wageningen University | |
ZHU, XINGUANG - Chinese Academy Of Sciences |
Submitted to: Frontiers in Plant Science
Publication Type: Review Article Publication Acceptance Date: 4/26/2017 Publication Date: 5/15/2017 Citation: Marshall-Colon, A., Long, S.P., Allen, D.K., Allen, G.D., Beard, D., Benes, B., Caemmerer, S., Christensen, A., Cox, D.J., Hart, J., Hirst, P., Kannan, K., Katz, D.S., Lynch, J., Millar, A., Panneerselvan, B., Price, N., Prusinkiewicz, P., Raila, D., Shekar, R.G., Shrivastava, S., Shukla, D., Srinivasan, V., Stitt, M., Turk, M.J., Voit, E.O., Wang, Y., Yin, X., Zhu, X. 2017. Crops in silico: Generating virtual crops using an integrative and multi-scale modeling platform. Frontiers in Plant Science. 8:786. doi: 10.3389/fpls.2017.00786. Interpretive Summary: Technical Abstract: There are currently 795 million hungry people in the world and 98 percent of them are in developing countries. Food demand is expected to increase by 70% by 2050. With a reduction in arable land, decreases in water availability, and an increasing impact of climate change, innovative technologies are required to sustainably improve crop yield. A biologically informed computational framework is critical to increasing food production under different climate scenarios and resource constraints. Multi-scale models can facilitate whole plant simulations of systems, linking gene networks, protein synthesis, metabolic pathways, physiology, growth, and development. These models have the potential to fill in missing mechanistic details and generate new testable hypotheses for directed engineering efforts. Outcomes from these models will accelerate efforts to improve plant yield and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes, and builds on the achievements in systems modeling of microbial and mammalian organisms. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. Here, we introduce Crops in silico, an integrative and multi-scale modeling platform as a solution to combine isolated modeling efforts toward the generation of a virtual plant, open and accessible to the entire plant biology community. |