首页|Reports on Plant Diseases and Conditions from University of Southern California (USC) Provide New Insights (Machine Learning-based Identification of General Tra nscriptional Predictors for Plant Disease)
Reports on Plant Diseases and Conditions from University of Southern California (USC) Provide New Insights (Machine Learning-based Identification of General Tra nscriptional Predictors for Plant Disease)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Plant Diseases and Conditions. According to newsreporting out of Los Angeles, C alifornia, by NewsRx editors, research stated, “This study investigatedthe gene ralizability of Arabidopsis thaliana immune responses across diverse pathogens, including Botrytiscinerea, Sclerotinia sclerotiorum, and Pseudomonas syringae, using a data-driven, machine learning approach.Machine learning models were tra ined to predict disease development from early transcriptionalresponses.”
Los AngelesCaliforniaUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningPla nt Diseases and ConditionsPlant Physiological PhenomenaUniversity of Souther n California (USC)
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