A new spatial transcriptomic technology captures RNA patterns without requiring expensive imaging ...
Graph Convolutional Networks (GCNs) are widely applied for spatial domain identification in spatial transcriptomics (ST), where node representations are learned by aggregating information from ...
Abstract: Recent advancements in spatial transcriptomics technology have enabled the capture of gene expression profiles while maintaining spatial information. Accurately identifying spatial ...
Adaptive Weighting Contrastive Learning for Spatial Domain Identification in Spatial Transcriptomics
Abstract: The rapid advancement of spatial transcriptomics has enabled the joint analysis of gene expression and spatial location data. This integration opens new avenues for uncovering tissue ...
This open access article is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This work is licensed under a Creative Commons Attribution 4.0 International ...
New simulator and computational tools generate realistic ‘virtual tissues’ and map cell-to-cell ‘conversations’ from spatial transcriptomics data, potentially accelerating AI-driven discoveries in ...
Dr. Hailing Shi to apply 3D spatial multi-omics to decode RNA regulation in the human brain and neurodegenerative diseases BOSTON, Jan. 28, 2026 /PRNewswire/ -- Stellaromics, a pioneer in ...
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