Cancer driver mutation prediction through Bayesian integration of multi-omic data

Identification of cancer driver mutations is critical for advancing cancer research and personalized medicine. Due to inter-tumor genetic heterogeneity, many driver mutations occur at low frequencies, which make it challenging to distinguish them from passenger mutations. Here, we show that a novel...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Zixing, Ng, Kwok-Shing, Chen, Tenghui, Kim, Tae-Beom, Wang, Fang, Shaw, Kenna, Scott, Kenneth L., Meric-Bernstam, Funda, Mills, Gordon B., Chen, Ken
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5940219/
https://www.ncbi.nlm.nih.gov/pubmed/29738578
http://dx.doi.org/10.1371/journal.pone.0196939

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5940219/
https://www.ncbi.nlm.nih.gov/pubmed/29738578
http://dx.doi.org/10.1371/journal.pone.0196939

Ejemplares similares