Cargando…
Detecting phenotype-driven transitions in regulatory network structure
Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense “communities” of genes that carry...
Autores principales: | Padi, Megha, Quackenbush, John |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5908977/ https://www.ncbi.nlm.nih.gov/pubmed/29707235 http://dx.doi.org/10.1038/s41540-018-0052-5 |
Ejemplares similares
-
Integrating transcriptional and protein interaction networks to prioritize condition-specific master regulators
por: Padi, Megha, et al.
Publicado: (2015) -
Generating Ensembles of Gene Regulatory Networks to Assess Robustness of Disease Modules
por: Lim, James T., et al.
Publicado: (2021) -
Estimating drivers of cell state transitions using gene regulatory network models
por: Schlauch, Daniel, et al.
Publicado: (2017) -
Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks
por: Fischer, Martin, et al.
Publicado: (2016) -
The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks
por: Ben Guebila, Marouen, et al.
Publicado: (2023)