XGDAG: explainable gene-disease associations via graph neural networks.
Andrea MastropietroGianluca De CarloAris AnagnostopoulosPublished in: Bioinform. (2023)
Keyphrases
- neural network
- gene gene
- biological entities
- microarray
- genetic variation
- disease genes
- pattern recognition
- candidate genes
- random walk
- gene networks
- protein protein interaction networks
- neural network model
- dna microarray
- association rules
- graph theory
- weighted graph
- graph representation
- graph structure
- gene expression
- gene function
- gene ontology
- sequence data
- artificial neural networks
- fuzzy logic
- directed graph
- gene expression data
- biomedical literature
- genetic algorithm
- differentially expressed genes
- high throughput
- gene sets
- biological knowledge
- biologically meaningful
- multilayer perceptron
- complex diseases
- genome wide association studies
- network model
- back propagation
- biological processes
- human genome
- graph model