Cargando…
MSEA: detection and quantification of mutation hotspots through mutation set enrichment analysis
Many cancer genes form mutation hotspots that disrupt their functional domains or active sites, leading to gain- or loss-of-function. We propose a mutation set enrichment analysis (MSEA) implemented by two novel methods, MSEA-clust and MSEA-domain, to predict cancer genes based on mutation hotspot p...
Autores principales: | Jia, Peilin, Wang, Quan, Chen, Qingxia, Hutchinson, Katherine E, Pao, William, Zhao, Zhongming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4226881/ https://www.ncbi.nlm.nih.gov/pubmed/25348067 http://dx.doi.org/10.1186/s13059-014-0489-9 |
Ejemplares similares
-
VERSE: a novel approach to detect virus integration in host genomes through reference genome customization
por: Wang, Qingguo, et al.
Publicado: (2015) -
Patterns and processes of somatic mutations in nine major cancers
por: Jia, Peilin, et al.
Publicado: (2014) -
Data-driven modelling of mutational hotspots and in silico predictors in hypertrophic cardiomyopathy
por: Waring, Adam, et al.
Publicado: (2021) -
A full-proteome, interaction-specific characterization of mutational hotspots across human cancers
por: Chen, Siwei, et al.
Publicado: (2022) -
MSEA: a web-based tool to identify biologically meaningful patterns in quantitative metabolomic data
por: Xia, Jianguo, et al.
Publicado: (2010)