Cargando…
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...
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: | |
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 |
Ejemplares similares
-
Author Correction: Functionally Enigmatic Genes in Cancer: Using TCGA Data to Map the Limitations of Annotations
por: Maertens, Alexandra, et al.
Publicado: (2020) -
Weighted Gene Correlation Network Analysis (WGCNA) Reveals Novel Transcription Factors Associated With Bisphenol A Dose-Response
por: Maertens, Alexandra, et al.
Publicado: (2018) -
Similarities and Differences in Gene Expression Networks Between the Breast Cancer Cell Line Michigan Cancer Foundation-7 and Invasive Human Breast Cancer Tissues
por: Tran, Vy, et al.
Publicado: (2021) -
Analysis of Public Oral Toxicity Data from REACH Registrations 2008–2014
por: Luechtefeld, Thomas, et al.
Publicado: (2016) -
Analysis of Publically Available Skin Sensitization Data from REACH Registrations 2008–2014
por: Luechtefeld, Thomas, et al.
Publicado: (2016)