GMFGRN: a matrix factorization and graph neural network approach for gene regulatory network inference.
Shuo LiYan LiuLong-Chen ShenHe YanJiangning SongDong-Jun YuPublished in: Briefings Bioinform. (2024)
Keyphrases
- matrix factorization
- gene regulatory networks
- neural network
- undirected graphical models
- network model
- dynamic bayesian networks
- collaborative filtering
- bayesian inference
- graphical models
- recommender systems
- gene expression data
- graph structure
- reverse engineering
- missing data
- factorization methods
- negative matrix factorization
- factor analysis
- conditional random fields
- probabilistic model
- structure learning
- gene expression
- exact inference
- factor graphs
- bayesian networks
- biological data
- belief propagation
- approximate inference
- markov networks
- data sets
- statistical analysis
- probabilistic inference