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Using Transcriptional Signatures to Find Cancer Drivers with LURE
Cancer genome projects have produced multidimensional datasets on thousands of samples. Yet, depending on the tumor type, 5–50% of samples have no known driving event. We introduce a semi-supervised method called Learning UnRealized Events (LURE) that uses a progressive label learning framework and...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6924983/ https://www.ncbi.nlm.nih.gov/pubmed/31797609 |