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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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| Pubblicato in: | Nat Genet |
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| Autori principali: | , , , , , , , , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2020
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| Soggetti: | |
| Accesso online: | 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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