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 ...
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 ...
Abstract: Spatial domain identification is a central task in spatial transcriptomics (ST) data analysis. We present GDST, a novel graph contrastive learning framework that leverages graph diffusion to ...
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 ...
aDivision of Rheumatology, Department of Internal Medicine, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, 510630, China bDepartment of Endocrinology and Metabolism, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results