Predicting Monoterpene Indole Alkaloid-Related Genes from Expression Data with Artificial Neural Networks

Thomas Dugé de Bernonville; Emily Amor Stander; Géraud Dugé de Bernonville; Sébastien Besseau; Vincent Courdavault

doi:10.1007/978-1-0716-2349-7_10

Book Sections Year : 2022

Predicting Monoterpene Indole Alkaloid-Related Genes from Expression Data with Artificial Neural Networks

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Thomas Dugé de Bernonville

Function : Author

Biomolécules et biotechnologies végétales

Emily Amor Stander

Function : Author

Biomolécules et biotechnologies végétales

Géraud Dugé de Bernonville

Function : Author

Sébastien Besseau

Function : Author

Biomolécules et biotechnologies végétales

Vincent Courdavault

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Biomolécules et biotechnologies végétales

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Life Sciences [q-bio]

Sébastien Besseau : Connect in order to contact the contributor

https://hal-univ-tours.archives-ouvertes.fr/hal-03916788

Submitted on : Saturday, December 31, 2022-10:35:34 AM

Last modification on : Sunday, January 1, 2023-3:43:09 AM

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hal-03916788 , version 1 (31-12-2022)

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HAL Id : hal-03916788 , version 1
DOI : 10.1007/978-1-0716-2349-7_10

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Thomas Dugé de Bernonville, Emily Amor Stander, Géraud Dugé de Bernonville, Sébastien Besseau, Vincent Courdavault. Predicting Monoterpene Indole Alkaloid-Related Genes from Expression Data with Artificial Neural Networks. Catharanthus roseus, 2505, Springer US, pp.131-140, 2022, Methods in Molecular Biology, ⟨10.1007/978-1-0716-2349-7_10⟩. ⟨hal-03916788⟩

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Predicting Monoterpene Indole Alkaloid-Related Genes from Expression Data with Artificial Neural Networks

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