Cargando…
A Bayesian model for identifying cancer subtypes from paired methylation profiles
Aberrant DNA methylation is the most common molecular lesion that is crucial for the occurrence and development of cancer, but has thus far been underappreciated as a clinical tool for cancer classification, diagnosis or as a guide for therapeutic decisions. Partly, this has been due to a lack of pr...
Autores principales: | Fan, Yetian, S Chan, April, Zhu, Jun, Yi Leung, Suet, Fan, Xiaodan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9851340/ https://www.ncbi.nlm.nih.gov/pubmed/36575828 http://dx.doi.org/10.1093/bib/bbac568 |
Ejemplares similares
-
Sample-specific perturbation of gene interactions identifies breast cancer subtypes
por: Chen, Yuanyuan, et al.
Publicado: (2020) -
Hierarchical cell-type identifier accurately distinguishes immune-cell subtypes enabling precise profiling of tissue microenvironment with single-cell RNA-sequencing
por: Lee, Joongho, et al.
Publicado: (2023) -
Scoring personalized molecular portraits identify Systemic Lupus Erythematosus subtypes and predict individualized drug responses, symptomatology and disease progression
por: Toro-Domínguez, Daniel, et al.
Publicado: (2022) -
Discovering gene regulatory networks of multiple phenotypic groups using dynamic Bayesian networks
por: Suter, Polina, et al.
Publicado: (2022) -
NCAE: data-driven representations using a deep network-coherent DNA methylation autoencoder identify robust disease and risk factor signatures
por: Martínez-Enguita, David, et al.
Publicado: (2023)