De-MISTED: Image-based classification of erroneous multiple sequence alignments using convolutional neural networks - CNRS - Centre national de la recherche scientifique
Journal Articles Applied Intelligence Year : 2023

De-MISTED: Image-based classification of erroneous multiple sequence alignments using convolutional neural networks

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Computer Science [cs]
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Julie Thompson  : Connect in order to contact the contributor

https://cnrs.hal.science/hal-04253859

Submitted on : Monday, October 23, 2023-10:41:34 AM

Last modification on : Tuesday, May 14, 2024-10:54:13 AM

Long-term archiving on : Wednesday, January 24, 2024-6:27:53 PM

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hal-04253859 , version 1 (23-10-2023)

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Hiba Khodji, Pierre Collet, Julie D. Thompson, Anne Jeannin-Girardon. De-MISTED: Image-based classification of erroneous multiple sequence alignments using convolutional neural networks. Applied Intelligence, 2023, 53 (15), pp.18806-18820. ⟨10.1007/s10489-022-04390-7⟩. ⟨hal-04253859⟩

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