Cargando…
Bayesian module identification from multiple noisy networks
BACKGROUND AND MOTIVATIONS: Module identification has been studied extensively in order to gain deeper understanding of complex systems, such as social networks as well as biological networks. Modules are often defined as groups of vertices in these networks that are topologically cohesive with simi...
Autores principales: | Zamani Dadaneh, Siamak, Qian, Xiaoning |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4744266/ https://www.ncbi.nlm.nih.gov/pubmed/26893596 http://dx.doi.org/10.1186/s13637-016-0038-9 |
Ejemplares similares
-
Bayesian gamma-negative binomial modeling of single-cell RNA sequencing data
por: Dadaneh, Siamak Zamani, et al.
Publicado: (2020) -
Covariate-dependent negative binomial factor analysis of RNA sequencing data
por: Zamani Dadaneh, Siamak, et al.
Publicado: (2018) -
Optimal clustering with missing values
por: Boluki, Shahin, et al.
Publicado: (2019) -
A Leaky Noisy-OR Bayesian Network Applied to Genetic Counseling in Dogs
por: Detilleux, Johann. C.
Publicado: (2020) -
Batched Bayesian
Optimization for Drug Design in Noisy
Environments
por: Bellamy, Hugo, et al.
Publicado: (2022)