CUDAGRN: Parallel Speedup of Inferring Large Gene Regulatory Networks from Expression Data Using Random Forest.
Seyed Ziaeddin AlborziD. A. K. MadurangaRui FanJagath C. RajapakseJie ZhengPublished in: PRIB (2014)
Keyphrases
- random forest
- gene regulatory networks
- reverse engineering
- gene expression data
- network model
- decision trees
- biological data
- feature set
- dynamic bayesian networks
- cancer classification
- bayesian inference
- ensemble methods
- multi label
- base classifiers
- higher order
- data mining
- microarray
- software engineering
- high dimensional
- bayesian networks
- structure learning
- learning algorithm
- machine learning