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A recent technology breakthrough in spatial molecular profiling has enabled the comprehensive molecular characterizations of single cells while preserving spatial information. It provides new opportunities to delineate how cells from…

Applications · Statistics 2021-10-07 Xi Jiang , Qiwei Li , Guanghua Xiao

The location, timing, and abundance of gene expression (both mRNA and proteins) within a tissue define the molecular mechanisms of cell functions. Recent technology breakthroughs in spatial molecular profiling, including imaging-based…

Applications · Statistics 2020-12-10 Qiwei Li , Minzhe Zhang , Yang Xie , Guanghua Xiao

Identifying genes that display spatial patterns is critical to investigating expression interactions within a spatial context and further dissecting biological understanding of complex mechanistic functionality. Despite the increase in…

Methodology · Statistics 2025-10-06 Mingcong Wu , Yang Li , Shuangge Ma , Mengyun Wu

The advent of next-generation sequencing-based spatially resolved transcriptomics (SRT) techniques has reshaped genomic studies by enabling high-throughput gene expression profiling while preserving spatial and morphological context.…

Applications · Statistics 2023-12-14 Bencong Zhu , Guanyu Hu , Yang Xie , Lin Xu , Xiaodan Fan , Qiwei Li

Spatially resolved transcriptomics is a fast-developing set of technologies that enables the measurement of localized gene expression across spatial locations in a sample. Detecting spatially varying genes is critical for analyzing such…

Applications · Statistics 2026-04-22 Pritam Dey , Rajarshi Guhaniyogi , Yang Ni , Bani K. Mallick

Identifying disease-indicative genes is critical for deciphering disease mechanisms and has attracted significant interest in biomedical research. Spatial transcriptomics offers unprecedented insights for the detection of disease-specific…

Methodology · Statistics 2024-09-05 Qicheng Zhao , Qihuang Zhang

Single-cell RNA-sequencing technologies may provide valuable insights to the understanding of the composition of different cell types and their functions within a tissue. Recent technologies such as spatial transcriptomics, enable the…

Applications · Statistics 2023-05-16 Arhit Chakrabarti , Yang Ni , Bani K. Mallick

Spatial transcriptomics technologies enable the measurement of gene expression with spatial context, providing opportunities to understand how gene regulatory networks vary across tissue regions. However, existing graphical models focus…

Methodology · Statistics 2025-12-15 Trisha Dawn , Yang Ni

With the emergence of advanced spatial transcriptomic technologies, there has been a surge in research papers dedicated to analyzing spatial transcriptomics data, resulting in significant contributions to our understanding of biology. The…

Genomics · Quantitative Biology 2024-04-11 Sikta Das Adhikari , Jiaxin Yang , Jianrong Wang , Yuehua Cui

Advances in spatial transcriptomics (ST) technologies enable systematic molecular characterization of tumor microenvironment, tumor gradients and gene regulatory networks. Cancer progression is known to vary along pathological gradients,…

Spatial transcriptomics measures the expression of thousands of genes in a tissue sample while preserving its spatial structure. This class of technologies has enabled the investigation of the spatial variation of gene expressions and their…

Methodology · Statistics 2025-10-23 Andrea Sottosanti , Davide Risso , Francesco Denti

Spatial variable genes (SVGs) reveal critical information about tissue architecture, cellular interactions, and disease microenvironments. As spatial transcriptomics (ST) technologies proliferate, accurately identifying SVGs across diverse…

Applications · Statistics 2025-10-21 Jiawen Chen , Jinwei Zhang , Dongshen Peng , Yutong Song , Aitong Ruan , Yun Li , Didong Li

Recent advancements in spatial transcriptomics technologies allow researchers to simultaneously measure RNA expression levels for hundreds to thousands of genes while preserving spatial information within tissues, providing critical…

Methodology · Statistics 2025-07-31 Catherine Higgins , Jingyi Jessica Li , Michelle Carey

Spatial Transcriptomics is a novel technology that aligns histology images with spatially resolved gene expression profiles. Although groundbreaking, it struggles with gene capture yielding high corruption in acquired data. Given potential…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Gabriel Mejia , Daniela Ruiz , Paula Cárdenas , Leonardo Manrique , Daniela Vega , Pablo Arbeláez

Spatial transcriptomics studies are becoming increasingly large and commonplace, necessitating simultaneous analysis of a large number of spatially resolved variables. Correspondingly, a diverse range of methodologies have been proposed to…

Quantitative Methods · Quantitative Biology 2025-09-09 James Boyle , Gregory Hamm , Eleanor Williams , Robin JG Hartman , Magnus Soderburg , Ian Henry , Michael Casey

Spatial transcriptomics is a modern sequencing technology that allows the measurement of the activity of thousands of genes in a tissue sample and map where the activity is occurring. This technology has enabled the study of the so-called…

Methodology · Statistics 2022-09-15 Andrea Sottosanti , Davide Risso

In the analysis of spatially resolved transcriptomics data, detecting spatially variable genes (SVGs) is crucial. Numerous computational methods exist, but varying SVG definitions and methodologies lead to incomparable results. We review 33…

Quantitative Methods · Quantitative Biology 2024-10-04 Guanao Yan , Shuo Harper Hua , Jingyi Jessica Li

Spatial transcriptomics is a technology that captures gene expression levels at different spatial locations, widely used in tumor microenvironment analysis and molecular profiling of histopathology, providing valuable insights into…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Junzhuo Liu , Markus Eckstein , Zhixiang Wang , Friedrich Feuerhake , Dorit Merhof

Spatial transcriptomics (ST) technologies enable transcriptome-wide gene expression profiling while preserving spatial resolution, offering unprecedented opportunities to uncover complex spatial structures. Due to the ultra-high…

Applications · Statistics 2026-03-11 Changhu Wang , Qiyun Huang , Zihao Chen , Jin Liu , Ruibin Xi

Spatial transcriptomics allows researchers to visualize and analyze gene expression within the precise location of tissues or cells. It provides spatially resolved gene expression data but often lacks cellular resolution, necessitating cell…

Quantitative Methods · Quantitative Biology 2025-10-27 Jiasen Zhang , Xi Qiao , Liangliang Zhang , Weihong Guo
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