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.
https://hal-amu.archives-ouvertes.fr/hal-03142946
Contributor : Sébastien Poulain <>
Submitted on : Tuesday, February 16, 2021 - 2:02:10 PM Last modification on : Thursday, February 18, 2021 - 3:28:27 AM
Files
Restricted access
To satisfy the distribution rights of the publisher, the document is embargoed
until : 2021-03-14
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⟩