Attention-guided variational graph autoencoders reveal heterogeneity in spatial transcriptomics.
Lixin LeiKaitai HanZijun WangChaojing ShiZhenghui WangRuoyan DaiZhiwei ZhangMengqiu WangQianjin GuoPublished in: Briefings Bioinform. (2024)
Keyphrases
- spatio temporal
- denoising
- graph theory
- spatial information
- graph representation
- image segmentation
- spatial data
- graph structure
- directed acyclic graph
- graph model
- structured data
- weighted graph
- spatial relationships
- directed graph
- spatial and temporal
- random walk
- graph mining
- neural network
- graph based algorithm
- link analysis
- bipartite graph
- spatial relations
- spatial databases
- spatial distribution
- connected components
- graph theoretic
- optical flow