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Artificial intelligence applied to the production of high-added-value dinoflagellates toxins

Abstract : Trade in high value-added toxins for therapeutic and biological use is expanding. These toxins are generally derived from microalgae belonging to the dinoflagellate family. Due to the difficulties to grow these sensitive planktonic species and to the complexity of methods used to synthesize these molecules, which are generally complex chemical structures, biotoxin manufacturers called on artificial intelligence technologies. Through the development of specific learning neural networks applied to each phases of biotoxin production: photo-bioreactors operating at optimal yield;-new chemical synthesis research processes;-toxin biosynthetic research pathways offering shortcut possibilities, manufacturing processes have been greatly improved.
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Submitted on : Tuesday, February 16, 2021 - 2:02:10 PM
Last modification on : Monday, January 17, 2022 - 1:23:27 PM
Long-term archiving on: : Monday, May 17, 2021 - 7:40:22 PM


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Jean-Louis Kraus. Artificial intelligence applied to the production of high-added-value dinoflagellates toxins. AI & Society: Knowledge, Culture and Communication, Springer Verlag, 2020, 35 (4), pp.851-855. ⟨10.1007/s00146-020-00959-3⟩. ⟨hal-03142946⟩



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