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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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Bibliografiske detaljer
Udgivet i:Nat Genet
Main Authors: 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
Format: Artigo
Sprog:Inglês
Udgivet: 2020
Fag:
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7610388/
https://ncbi.nlm.nih.gov/pubmed/32879509
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41588-020-0675-5
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