Combining exome and gene expression datasets in one graphical model of disease to empower the discovery of disease mechanisms.
Aziz M. MezliniFabio FuligniAdam ShlienAnna GoldenbergPublished in: CoRR (2015)
Keyphrases
- markov random field
- belief propagation
- graphical models
- conditional random fields
- markov networks
- approximate inference
- factor graphs
- probabilistic graphical models
- probabilistic model
- probabilistic inference
- structure learning
- gene expression data
- random variables
- gene expression datasets
- data mining
- data sets
- conditional dependencies
- conditional independence
- microarray
- bayesian networks
- real world