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Spatial Transcriptomics enables mapping of gene expression within its native tissue context, but current platforms measure only a limited set of genes due to experimental constraints and excessive costs. To overcome this, computational…

Genomics · Quantitative Biology 2025-11-20 Amit Kumar , Maninder Kaur , Raghvendra Mall , Sukrit Gupta

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 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 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 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

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 is an emerging technology that aligns histopathology images with spatially resolved gene expression profiling. It holds the potential for understanding many diseases but faces significant bottlenecks such as…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Gabriel Mejia , Paula Cárdenas , Daniela Ruiz , Angela Castillo , Pablo Arbeláez

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

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

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

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

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

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

Spatial transcriptomics enables simultaneous measurement of gene expression and tissue morphology, offering unprecedented insights into cellular organization and disease mechanisms. However, the field lacks comprehensive benchmarks for…

Spatial transcriptomics offers spatially resolved gene expression profiling within tissue sections, but its cost and limited throughput hinder large-scale deployment. To extend this capability to routine practice, recent computational…

Machine Learning · Computer Science 2026-05-07 Keunho Byeon , Jin Tae Kwak

The spatial location of cells within tissues and organs is crucial for the manifestation of their specific functions.Spatial transcriptomics technology enables comprehensive measurement of the gene expression patterns in tissues while…

Quantitative Methods · Quantitative Biology 2024-07-12 Shuailin Xue , Fangfang Zhu , Changmiao Wang , Wenwen Min

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

Spatial Transcriptomics (ST) offers spatially resolved gene expression but remains costly. Predicting expression directly from widely available Hematoxylin and Eosin (H&E) stained images presents a cost-effective alternative. However, most…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Jiarui Ouyang , Yihui Wang , Yihang Gao , Yingxue Xu , Shu Yang , Hao Chen

Recent years have witnessed remarkable progress in multimodal learning within computational pathology. Existing models primarily rely on vision and language modalities; however, language alone lacks molecular specificity and offers limited…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Minghao Han , Dingkang Yang , Linhao Qu , Zizhi Chen , Gang Li , Han Wang , Jiacong Wang , Lihua Zhang
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