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Machine learning and feature selection for drug response prediction in precision oncology applications
In-depth modeling of the complex interplay among multiple omics data measured from cancer cell lines or patient tumors is providing new opportunities toward identification of tailored therapies for individual cancer patients. Supervised machine learning algorithms are increasingly being applied to t...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer Berlin Heidelberg
2018
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6381361/ https://www.ncbi.nlm.nih.gov/pubmed/30097794 http://dx.doi.org/10.1007/s12551-018-0446-z |