High throughput predictive bioenergetics through statistical machine learning for big-data to assess biological responses to environmental stressors

PI: Jayasundara Nishad (Marine Science, UMaine) Sector: Biology, Data Science Partners: UMaine Abstract: The goal of this research is to build a team of undergraduates to integrate biological sciences with big-data statistical approaches to develop a commercializable statistical tool that can predictively compute the capacity of an organism to maintain energy homeostasis when exposed to toxicants and other stressors read more High throughput predictive bioenergetics through statistical machine learning for big-data to assess biological responses to environmental stressors