Creating artificial human genomes using generative neural networks

Generative models have shown breakthroughs in a wide spectrum of domains due to recent advancements in machine learning algorithms and increased computational power. Despite these impressive achievements, the ability of generative models to create realistic synthetic data is still under-exploited in...

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Detalles Bibliográficos
Autores principales: Yelmen, Burak, Decelle, Aurélien, Ongaro, Linda, Marnetto, Davide, Tallec, Corentin, Montinaro, Francesco, Furtlehner, Cyril, Pagani, Luca, Jay, Flora
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861435/
https://www.ncbi.nlm.nih.gov/pubmed/33539374
http://dx.doi.org/10.1371/journal.pgen.1009303

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861435/
https://www.ncbi.nlm.nih.gov/pubmed/33539374
http://dx.doi.org/10.1371/journal.pgen.1009303

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