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Providing an optimized model to detect driver genes from heterogeneous cancer samples using restriction in subspace learning
Extracting the drivers from genes with mutation, and segregation of driver and passenger genes are known as the most controversial issues in cancer studies. According to the heterogeneity of cancer, it is not possible to identify indicators under a group of associated drivers, in order to identify a...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080706/ https://www.ncbi.nlm.nih.gov/pubmed/33911156 http://dx.doi.org/10.1038/s41598-021-88548-2 |