A graphical model approach for inferring large-scale networks integrating gene expression and genetic polymorphism.
Jen-hwa ChuScott T. WeissVincent J. CareyBenjamin A. RabyPublished in: BMC Syst. Biol. (2009)
Keyphrases
- graphical models
- gene expression
- microarray
- belief propagation
- gene expression data
- probabilistic model
- probabilistic graphical models
- approximate inference
- probabilistic inference
- random variables
- biological knowledge
- biological processes
- microarray data
- gene interactions
- structure learning
- gene expression patterns
- conditional random fields
- factor graphs
- gene expression profiles
- belief networks
- markov networks
- conditional independence
- regulatory networks
- conditional dependencies
- bayesian networks
- transcription factors
- high throughput
- complex networks
- network structure
- network analysis
- binding sites
- gene selection
- dynamic bayesian networks
- message passing
- community structure
- information extraction
- high dimensional
- data analysis
- social networks