spatial transcriptomics st technologies (Spatial Transcriptomics Inc)
86
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Spatial Transcriptomics Inc
spatial transcriptomics st technologies
Spatial Transcriptomics St Technologies, supplied by Spatial Transcriptomics Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/spatial+transcriptomics+st+technology/spatial+st+technologies+transcriptomics/pm41611568-21-0-0
Average 86 stars, based on 1 article reviews
Spatial Transcriptomics St Technologies, supplied by Spatial Transcriptomics Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/spatial+transcriptomics+st+technology/spatial+st+technologies+transcriptomics/pm41611568-21-0-0
Average 86 stars, based on 1 article reviews
spatial transcriptomics st technologies - by Bioz Stars,
2026-09
86/100 stars
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Spatial Transcriptomics:Article Title: Deep Learning-Based Quality Control Using Subcellular RNA Spatial Distribution Patterns for Cell Segmentation in Spatial Transcriptomics Data. Article Snippet: Sequencing-based spatial transcriptomics (sST) techniques with high resolution enable transcriptome-wide RNA capture at subcellular resolution.. Although new cell segmentation methods for sST data are continually being developed, accurately assigning RNA spots to corresponding cells still presents significant challenges and there is a lack of quality control methods.. This work introduces a deep learning method for quality control of cell segmentation and improvement of the segmentation result. Article Title: Autoencoder Denoising for Network-Based Spatial Transcriptomics Data with Applications for Cell Signaling Estimation Article Snippet: .. Article Title: Inference of cell-type composition and single-cell spatial maps from spatial transcriptomics data with SWOT Article Snippet: .. Article Title: Heterogeneous graph contrastive learning for integration and alignment of spatial transcriptomics data. Article Snippet: .. Article Title: ST-FFPE-mIF: integrating spatial transcriptomics and multiplex immunofluorescence in formalin-fixed paraffin-embedded tissues using Stereo-seq Article Snippet: .. Article Title: Systematic benchmarking of high-throughput subcellular spatial transcriptomics platforms across human tumors Article Snippet: .. Driven by its transformative potential, Gene Expression:Article Title: Deep Learning-Based Quality Control Using Subcellular RNA Spatial Distribution Patterns for Cell Segmentation in Spatial Transcriptomics Data. Article Snippet: Sequencing-based spatial transcriptomics (sST) techniques with high resolution enable transcriptome-wide RNA capture at subcellular resolution.. Although new cell segmentation methods for sST data are continually being developed, accurately assigning RNA spots to corresponding cells still presents significant challenges and there is a lack of quality control methods.. This work introduces a deep learning method for quality control of cell segmentation and improvement of the segmentation result. Article Title: Inference of cell-type composition and single-cell spatial maps from spatial transcriptomics data with SWOT Article Snippet: .. Article Title: Heterogeneous graph contrastive learning for integration and alignment of spatial transcriptomics data. Article Snippet: .. Single Cell:Article Title: Deep Learning-Based Quality Control Using Subcellular RNA Spatial Distribution Patterns for Cell Segmentation in Spatial Transcriptomics Data. Article Snippet: Sequencing-based spatial transcriptomics (sST) techniques with high resolution enable transcriptome-wide RNA capture at subcellular resolution.. Although new cell segmentation methods for sST data are continually being developed, accurately assigning RNA spots to corresponding cells still presents significant challenges and there is a lack of quality control methods.. This work introduces a deep learning method for quality control of cell segmentation and improvement of the segmentation result. Expressing:Article Title: Inference of cell-type composition and single-cell spatial maps from spatial transcriptomics data with SWOT Article Snippet: .. Imaging:Article Title: Single-cell sequencing technology in renal cancer: insights into tumor biology and clinical application Article Snippet: .. |