Functionally Enigmatic Genes in Cancer: Using TCGA Data to Map the Limitations of Annotations

Cancer is a comparatively well-studied disease, yet despite decades of intense focus, we demonstrate here using data from The Cancer Genome Atlas that a substantial number of genes implicated in cancer are relatively poorly studied. Those genes will likely be missed by any data analysis pipeline, su...

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Detalles Bibliográficos
Autores principales: Maertens, Alexandra, Tran, Vy H., Maertens, Mikhail, Kleensang, Andre, Luechtefeld, Thomas H., Hartung, Thomas, Paller, Channing J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057977/
https://www.ncbi.nlm.nih.gov/pubmed/32139709
http://dx.doi.org/10.1038/s41598-020-60456-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057977/
https://www.ncbi.nlm.nih.gov/pubmed/32139709
http://dx.doi.org/10.1038/s41598-020-60456-x

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