Cargando…
Inferring tumor progression in large datasets
Identification of mutations of the genes that give cancer a selective advantage is an important step towards research and clinical objectives. As such, there has been a growing interest in developing methods for identification of driver genes and their temporal order within a single patient (intra-t...
Autores principales: | Mohaghegh Neyshabouri, Mohammadreza, Jun, Seong-Hwan, Lagergren, Jens |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577444/ https://www.ncbi.nlm.nih.gov/pubmed/33035204 http://dx.doi.org/10.1371/journal.pcbi.1008183 |
Ejemplares similares
-
ToMExO: A probabilistic tree-structured model for cancer progression
por: Mohaghegh Neyshabouri, Mohammadreza, et al.
Publicado: (2022) -
Inferring whole-genome histories in large population datasets
por: Kelleher, Jerome, et al.
Publicado: (2019) -
Probabilistic inference of lateral gene transfer events
por: Khan, Mehmood Alam, et al.
Publicado: (2016) -
Unified tumor growth mechanisms from multimodel inference and dataset integration
por: Beik, Samantha P., et al.
Publicado: (2023) -
Comparison of the accuracy of methods of computational haplotype inference using a large empirical dataset
por: Adkins, Ronald M
Publicado: (2004)