Structural identifiability of cyclic graphical models of biological networks with latent variables.
Yulin WangNa LuHongyu MiaoPublished in: BMC Syst. Biol. (2016)
Keyphrases
- latent variables
- graphical models
- biological networks
- probabilistic model
- random variables
- probabilistic graphical models
- approximate inference
- factor graphs
- belief propagation
- complex networks
- posterior distribution
- exact inference
- gene expression
- biological data
- probabilistic inference
- latent variable models
- structure learning
- conditional random fields
- gene regulatory networks
- bayesian inference
- bayesian networks
- link prediction
- belief networks
- hidden variables
- markov networks
- gaussian process
- conditional probabilities
- conditional independence
- directed acyclic graph
- generative model
- microarray
- data sets
- expectation maximization
- causal relationships
- causal models
- posterior probability
- social network analysis
- high throughput
- probability distribution
- high dimensional
- message passing