Deep learning on butterfly phenotypes tests evolution’s oldest mathematical model

Traditional anatomical analyses captured only a fraction of real phenomic information. Here, we apply deep learning to quantify total phenotypic similarity across 2468 butterfly photographs, covering 38 subspecies from the polymorphic mimicry complex of Heliconius erato and Heliconius melpomene. Euc...

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Detalles Bibliográficos
Autores principales: Hoyal Cuthill, Jennifer F., Guttenberg, Nicholas, Ledger, Sophie, Crowther, Robyn, Huertas, Blanca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2019
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6693915/
https://www.ncbi.nlm.nih.gov/pubmed/31453326
http://dx.doi.org/10.1126/sciadv.aaw4967

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6693915/
https://www.ncbi.nlm.nih.gov/pubmed/31453326
http://dx.doi.org/10.1126/sciadv.aaw4967

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