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https://www.selleckchem.com/products/17-AAG(Geldanamycin).html er, differences in the regulated genes, likely associated with ploidy and heterosis, highlighted the value of exploring its diversity for breeding. Different phenotypic responses were observed during drought stress among Miscanthus genotypes from different species, supporting differences in genetic adaption. The low number of DEGs and higher biomass yield in flooded conditions supported Miscanthus use in flooded land. The molecular processes regulated during drought were shared among Miscanthus species and consistent with functional categories known to be critical during drought stress in model organisms. However, differences in the regulated genes, likely associated with ploidy and heterosis, highlighted the value of exploring its diversity for breeding.Leveraging artificial intelligence (AI) approaches in animal health (AH) makes it possible to address highly complex issues such as those encountered in quantitative and predictive epidemiology, animal/human precision-based medicine, or to study host × pathogen interactions. AI may contribute (i) to diagnosis and disease case detection, (ii) to more reliable predictions and reduced errors, (iii) to representing more realistically complex biological systems and rendering computing codes more readable to non-computer scientists, (iv) to speeding-up decisions and improving accuracy in risk analyses, and (v) to better targeted interventions and anticipated negative effects. In turn, challenges in AH may stimulate AI research due to specificity of AH systems, data, constraints, and analytical objectives. Based on a literature review of scientific papers at the interface between AI and AH covering the period 2009-2019, and interviews with French researchers positioned at this interface, the present study explains the main AH areas where various AI approaches are currently mobilised, how it may contribute to renew AH research issues and remove methodological or

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