Graphical Models and Inference on Graphs in Genomics: Challenges of high-throughput data analysis.
Manohar ShamaiahSang Hyun LeeHaris VikaloPublished in: IEEE Signal Process. Mag. (2012)
Keyphrases
- high throughput
- graphical models
- biological data
- probabilistic inference
- graphical structure
- exact inference
- data analysis
- map inference
- graph structure
- bayesian networks
- belief networks
- factor graphs
- belief propagation
- systems biology
- directed acyclic
- probabilistic model
- microarray
- data acquisition
- genome wide
- loopy belief propagation
- approximate inference
- structural learning
- undirected graphical models
- random variables
- efficient inference algorithms
- probabilistic graphical models
- statistical inference
- chain graphs
- markov networks
- directed graphical models
- structure learning
- conditional random fields
- life sciences
- protein protein interactions
- mass spectrometry
- message passing
- flow cytometry
- data collection
- data mining
- dynamic bayesian networks
- conditional independence
- relational dependency networks
- possibilistic networks
- statistical relational learning
- markov logic networks
- knowledge discovery
- machine learning
- junction tree
- bayesian inference
- stereo matching
- gene expression
- low cost