aDepartment of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA bDivision of Molecular Psychiatry, Department of Psychiatry, Yale University School of Medicine, ...
The launch marks a fundamental shift in spatial biology — from 2D thin-section approaches that analyze partial cell layers to true 3D analysis that preserves the native organization of cells, ...
ArgenTag joins PacBio to enable instrument-free single-cell kits to support long-read isoform sequencing at single-cell ...
A new spatial transcriptomic technology captures RNA patterns without requiring expensive imaging ...
A new software tool, ovrlpy, improves quality control in spatial transcriptomics, a key technology in biomedical research. Developed by the Berlin Institute of Health at Charité (BIH) in international ...
Graph Convolutional Networks (GCNs) are widely applied for spatial domain identification in spatial transcriptomics (ST), where node representations are learned by aggregating information from ...
Gastric cancer (GC) develops through a sequence from chronic gastritis to intestinal metaplasia (IM) and carcinoma, with Helicobacter pylori (HP) as a key driver; however, the molecular mediators ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results