Cargando…
Bayesian correlated clustering to integrate multiple datasets
Motivation: The integration of multiple datasets remains a key challenge in systems biology and genomic medicine. Modern high-throughput technologies generate a broad array of different data types, providing distinct—but often complementary—information. We present a Bayesian method for the unsupervi...
Autores principales: | Kirk, Paul, Griffin, Jim E., Savage, Richard S., Ghahramani, Zoubin, Wild, David L. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3519452/ https://www.ncbi.nlm.nih.gov/pubmed/23047558 http://dx.doi.org/10.1093/bioinformatics/bts595 |
Ejemplares similares
-
Discovering transcriptional modules by Bayesian data integration
por: Savage, Richard S., et al.
Publicado: (2010) -
Accelerating Bayesian Hierarchical Clustering of Time Series Data with a Randomised Algorithm
por: Darkins, Robert, et al.
Publicado: (2013) -
R/BHC: fast Bayesian hierarchical clustering for microarray data
por: Savage, Richard S, et al.
Publicado: (2009) -
Bayesian non-parametrics and the probabilistic approach to modelling
por: Ghahramani, Zoubin
Publicado: (2013) -
Multiple kernel learning for integrative consensus clustering of omic datasets
por: Cabassi, Alessandra, et al.
Publicado: (2020)