A Maximum A Posteriori Probability and Time-Varying Approach for Inferring Gene Regulatory Networks from Time Course Gene Microarray Data.
Shing-Chow ChanLi ZhangHo-Chun WuKai Man TsuiPublished in: IEEE ACM Trans. Comput. Biol. Bioinform. (2015)
Keyphrases
- gene regulatory networks
- maximum a posteriori probability
- gene expression data
- reverse engineering
- markov random field
- network model
- biological data
- microarray
- map estimation
- gene expression
- bayesian inference
- dynamic bayesian networks
- parameter estimation
- structure learning
- high dimensionality
- software engineering
- microarray data
- pattern recognition
- microarray images
- high throughput
- database
- conditional random fields
- edge detection
- higher order
- pairwise
- face recognition
- data sets