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Recursive Random Lasso (RRLasso) for Identifying Anti-Cancer Drug Targets
Uncovering driver genes is crucial for understanding heterogeneity in cancer. L (1)-type regularization approaches have been widely used for uncovering cancer driver genes based on genome-scale data. Although the existing methods have been widely applied in the field of bioinformatics, they possess...
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| Publicado en: | PLoS One |
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| Autores principales: | , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Public Library of Science
2015
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4636151/ https://ncbi.nlm.nih.gov/pubmed/26544691 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0141869 |
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