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Article dans une revue Journal of Archaeological Science Année : 2021

Machine learning ATR-FTIR spectroscopy data for the screening of collagen for ZooMS analysis and mtDNA in archaeological bone

Manasij Pal Chowdhury
Kaustabh Datta Choudhury
Geneviève Pothier Bouchard
  • Fonction : Auteur
Julien Riel-Salvatore
Fabio Negrino
  • Fonction : Auteur
Stefano Benazzi
Brenna Frasier
  • Fonction : Auteur
Vicki Szabo
  • Fonction : Auteur
Ramona Harrison
George Hambrecht
  • Fonction : Auteur
Andrew C Kitchener
Roy A Wogelius
Michael Buckley

Résumé

Faunal remains from archaeological sites allow for the identification of animal species the enables the better understanding of the relationships between humans and animals, not only from their morphological information, but also from the ancient biomolecules (lipids, proteins, and DNA) preserved in these remains for thousands and even millions of years. However, due to the costs and efforts required for ancient biomolecular analysis, there has been considerable research into development of accurate and efficient screening approaches for archaeolog
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halshs-03869199, version 1 (24-11-2022)

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Manasij Pal Chowdhury, Kaustabh Datta Choudhury, Geneviève Pothier Bouchard, Julien Riel-Salvatore, Fabio Negrino, et al.. Machine learning ATR-FTIR spectroscopy data for the screening of collagen for ZooMS analysis and mtDNA in archaeological bone. Journal of Archaeological Science, 2021, 126, pp.105311. ⟨10.1016/j.jas.2020.105311⟩. ⟨halshs-03869199⟩
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