期刊
TRENDS IN BIOTECHNOLOGY
卷 37, 期 11, 页码 1217-1235出版社
ELSEVIER SCIENCE LONDON
DOI: 10.1016/j.tibtech.2019.05.007
关键词
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资金
- EU 7th Framework Programme - WATBIO [311929]
- Italian Ministry of Education
- University & Research Brain Gain Professorship
- Center for Bioenergy Innovation, a US Department of Energy Bioenergy Research Center - Office of Biological and Environmental Research in the DOE Office of Science
- DOE, Laboratory Directed Research and Development funding (ORNL AI Initiative Project) at the Oak Ridge National Laboratory [9613]
- DOE Office of Science User Facility [DE-AC05-00OR2272]
- US Department of Energy [DE-AC05-00OR22725]
Breeding crops for high yield and superior adaptability to new and variable climates is imperative to ensure continued food security, biomass production, and ecosystem services. Advances in genomics and phenomics are delivering insights into the complex biological mechanisms that underlie plant functions in response to environmental perturbations. However, linking genotype to phenotype remains a huge challenge and is hampering the optimal application of high throughput genomics and phenomics to advanced breeding. Critical to success is the need to assimilate large amounts of data into biologically meaningful interpretations. Here, we present the current state of genomics and field phenomics, explore emerging approaches and challenges for multiomics big data integration by means of next-generation (Next-Gen) artificial intelligence (AI), and propose a workable path to improvement.
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