INTERPRETING GENERATIVE ADVERSARIAL NETWORKS TO INFER NATURAL SELECTION FROM GENETIC DATA

Understanding natural selection in humans and other species is a major focus for the use of machine learning in population genetics. Existing methods rely on computationally intensive simulated training data. Unlike efficient neutral coalescent simulations for demographic inference, realistic simula...

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Detalles Bibliográficos
Autores principales: Riley, Rebecca, Mathieson, Iain, Mathieson, Sara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028936/
https://www.ncbi.nlm.nih.gov/pubmed/36945387
http://dx.doi.org/10.1101/2023.03.07.531546

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028936/
https://www.ncbi.nlm.nih.gov/pubmed/36945387
http://dx.doi.org/10.1101/2023.03.07.531546

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