Data management and modeling in plant biology

For those studying plant biology and how the environment affects it, the recognition of that study as being multidisciplinary, challenging, and vital is growing. However, as Krantz et al. point out in their 2021 paper published in Frontiers in Plant Science, that recognition alone is not enough. Given multi-omics research into plant biology and the environmental sciences over recent decades, as well as disparate data formats and management strategies across the many related disciplines, bringing this varied multidisciplinary data together for research is difficult, slowing the modern research process down. The authors review these incoherencies and discuss several ways in which ” a quantitative model of plant-environment interactions” is required to advance such research. After their introduction, the authors discuss important components of this model, including genome-scale metabolic network reconstruction, quantitative large-scale experiments on integrative platforms, quantitative analysis methods, and research data management systems. They conclude that these elements, and others, will help lead to more “efficient use of experimental findings.”

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