Cargando…
Identification of Common Driver Gene Modules and Associations between Cancers through Integrated Network Analysis
High‐throughput biological data has created an unprecedented opportunity for illuminating the mechanisms of tumor emergence and evolution. An important and challenging problem in deciphering cancers is to investigate the commonalities of driver genes and pathways and the associations between cancers...
Autores principales: | Gao, Bo, Zhao, Yue, Gao, Yonghang, Li, Guojun, Wu, Ling‐Yun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8414517/ https://www.ncbi.nlm.nih.gov/pubmed/34504716 http://dx.doi.org/10.1002/gch2.202100006 |
Ejemplares similares
-
MaxMIF: A New Method for Identifying Cancer Driver Genes through Effective Data Integration
por: Hou, Yingnan, et al.
Publicado: (2018) -
Identification of driver modules in pan-cancer via coordinating coverage and exclusivity
por: Gao, Bo, et al.
Publicado: (2017) -
Obstructive Sleep Apnea and Dementia-Common Gene Associations through Network-Based Identification of Common Driver Genes
por: Jeong, Hyun-Hwan, et al.
Publicado: (2021) -
Identification of ovarian cancer subtype-specific network modules and candidate drivers through an integrative genomics approach
por: Zhang, Di, et al.
Publicado: (2015) -
Prediction of Driver Modules via Balancing Exclusive Coverages of Mutations in Cancer Samples
por: Gao, Bo, et al.
Publicado: (2018)