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Variable selection for disease progression models: methods for oncogenetic trees and application to cancer and HIV
BACKGROUND: Disease progression models are important for understanding the critical steps during the development of diseases. The models are imbedded in a statistical framework to deal with random variations due to biology and the sampling process when observing only a finite population. Conditional...
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| Publicado no: | BMC Bioinformatics |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5539896/ https://ncbi.nlm.nih.gov/pubmed/28764644 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-017-1762-1 |
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