Subclonal reconstruction of tumors using machine learning and population genetics

The majority of cancer genomic data are generated from bulk samples composed of mixtures of cancer subpopulations, as well as normal cells. Subclonal reconstruction approaches based on machine learning aim to separate those subpopulations in a sample and reconstruct their evolutionary history. Howev...

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Detalles Bibliográficos
Autores principales: Caravagna, Giulio, Heide, Timon, Williams, Marc J., Zapata, Luis, Nichol, Daniel, Chkhaidze, Ketevan, Cross, William, Cresswell, George D., Werner, Benjamin, Acar, Ahmet, Chesler, Louis, Barnes, Chris P., Sanguinetti, Guido, Graham, Trevor A., Sottoriva, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610388/
https://www.ncbi.nlm.nih.gov/pubmed/32879509
http://dx.doi.org/10.1038/s41588-020-0675-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610388/
https://www.ncbi.nlm.nih.gov/pubmed/32879509
http://dx.doi.org/10.1038/s41588-020-0675-5

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