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...

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Detalles Bibliográficos
Autores principales: Haan, David, Tao, Ruikang, Friedl, Verena, Anastopoulos, Ioannis N, Wong, Christopher K, Weinstein, Alana S, Stuart, Joshua M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6924983/
https://www.ncbi.nlm.nih.gov/pubmed/31797609

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6924983/
https://www.ncbi.nlm.nih.gov/pubmed/31797609

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