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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

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

The technology to generate Spatially Resolved Transcriptomics (SRT) data is rapidly being improved and applied to investigate a variety of biological tissues. The ability to interrogate how spatially localised gene expression can lend new…

Quantitative Methods · Quantitative Biology 2021-08-04 Natalie Charitakis , Mirana Ramialison , Hieu T. Nim

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 has revolutionized tissue analysis by simultaneously mapping gene expression, spatial topography, and histological context across consecutive tissue sections, enabling systematic investigation of spatial…

Applications · Statistics 2025-10-24 Meng Zhou , Shuangge Ma , Mengyun Wu

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

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

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 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

Human and animal tissues consist of heterogeneous cell types that organize and interact in highly structured manners. Bulk and single-cell sequencing technologies remove cells from their original microenvironments, resulting in a loss of…

Quantitative Methods · Quantitative Biology 2022-02-08 Boxiang Liu , Yanjun Li , Liang Zhang

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

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

In order to understand the complexities of cellular biology, researchers are interested in two important metrics: the genetic expression information of cells and their spatial coordinates within a tissue sample. However, state-of-the art…

Machine Learning · Computer Science 2023-11-02 J. Ding , S. N. Zaman , P. Y. Chen , D. Wang

Several modern genomic technologies, such as DNA-Methylation arrays, measure spatially registered probes that number in the hundreds of thousands across multiplechromosomes. The measured probes are by themselves less interesting…

Applications · Statistics 2016-11-16 John Nagorski , Genevera I. Allen

Spatially resolved transcriptomics (ST) measures gene expression along with the spatial coordinates of the measurements. The analysis of ST data involves significant computation complexity. In this work, we propose gene expression…

Genomics · Quantitative Biology 2022-05-24 Zhuoyan Xu , Kris Sankaran

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

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 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 is a groundbreaking technology that integrates histology images with spatially resolved gene expression profiles. Among the various Spatial Transcriptomics techniques available, Visium has emerged as the most widely…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Daniela Ruiz , Paula Cárdenas , Leonardo Manrique , Daniela Vega , Gabriel M. Mejia , Pablo Arbeláez

Spatial studies of transcriptome provide biologists with gene expression maps of heterogeneous and complex tissues. However, most experimental protocols for spatial transcriptomics suffer from the need to select beforehand a small fraction…

Machine Learning · Computer Science 2019-05-08 Romain Lopez , Achille Nazaret , Maxime Langevin , Jules Samaran , Jeffrey Regier , Michael I. Jordan , Nir Yosef
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