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Spatial transcriptomics (ST) enables transcriptome-wide profiling while preserving the spatial context of tissues, offering unprecedented opportunities to study tissue organization and cell-cell interactions in situ. Despite recent…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Wei Wang , Quoc-Toan Ly , Chong Yu , Jun Bai

Spatial Transcriptomics (ST) provides spatially resolved gene expression profiles within intact tissue architecture, enabling molecular analysis in histological context. However, the high cost, limited throughput, and restricted data…

Machine Learning · Computer Science 2026-03-31 Yaoyu Fang , Jiahe Qian , Xinkun Wang , Lee A. Cooper , Bo Zhou

Spatial Transcriptomics (ST) profiles thousands of gene expression values at discrete spots with precise coordinates on tissue sections, preserving spatial context essential for clinical and pathological studies. With rising sequencing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yishun Zhu , Jiaxin Qi , Jian Wang , Yuhua Zheng , Jianqiang Huang

Spatial Transcriptomics (ST) reveals the spatial distribution of gene expression in tissues, offering critical insights into biological processes and disease mechanisms. However, the high cost, limited coverage, and technical complexity of…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Yi Niu , Jiashuai Liu , Yingkang Zhan , Jiangbo Shi , Di Zhang , Marika Reinius , Ines Machado , Mireia Crispin-Ortuzar , Jialun Wu , Chen Li , Zeyu Gao

Spatial transcriptomics (ST) enables the visualization of gene expression within the context of tissue morphology. This emerging discipline has the potential to serve as a foundation for developing tools to design precision medicines.…

Image and Video Processing · Electrical Eng. & Systems 2024-11-12 Shivam Kumar , Samrat Chatterjee

Spatial transcriptomics (ST) provides essential spatial context by mapping gene expression within tissue, enabling detailed study of cellular heterogeneity and tissue organization. However, aligning ST data with histology images poses…

Spatial transcriptomics (ST) profiles gene expression across a tissue section while preserving the spatial coordinates. Because current ST technologies typically profile two-dimensional tissue slices, integrating and aligning slices from…

Quantitative Methods · Quantitative Biology 2026-03-20 Yaqi Wu , Jingfeng Wang , Xin Maizie Zhou , Yanxiang Zhao , Zixuan Cang

Spatial Transcriptomics (ST) technologies provide biologists with rich insights into single-cell biology by preserving spatial context of cells. Building foundational models for ST can significantly enhance the analysis of vast and complex…

Genomics · Quantitative Biology 2025-07-24 Suyuan Zhao , Yizhen Luo , Ganbo Yang , Yan Zhong , Hao Zhou , Zaiqing Nie

Spatial transcriptomics (ST) is an emerging technology that enables researchers to investigate the molecular relationships underlying tissue morphology. However, acquiring ST data remains prohibitively expensive, and traditional fixed-grid…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Junchao Zhu , Ruining Deng , Junlin Guo , Tianyuan Yao , Chongyu Qu , Juming Xiong , Siqi Lu , Zhengyi Lu , Yanfan Zhu , Marilyn Lionts , Yuechen Yang , Yalin Zheng , Yu Wang , Shilin Zhao , Haichun Yang , Yuankai Huo

The rapid advancement of spatial transcriptomics (ST), i.e., spatial gene expressions, has made it possible to measure gene expression within original tissue, enabling us to discover molecular mechanisms. However, current ST platforms…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Xiaofei Wang , Stephen Price , Chao Li

Spatial Transcriptomics (ST) merges the benefits of pathology images and gene expression, linking molecular profiles with tissue structure to analyze spot-level function comprehensively. Predicting gene expression from histology images is a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Chen Zhang , Yilu An , Ying Chen , Hao Li , Xitong Ling , Lihao Liu , Junjun He , Yuxiang Lin , Zihui Wang , Rongshan Yu

Spatial transcriptomics (ST) has revolutionized biomedical research by enabling high resolution gene expression profiling within tissues. However, the high cost and scarcity of high resolution ST data remain significant challenges. We…

Computer Vision and Pattern Recognition · Computer Science 2025-07-24 Yaoyu Fang , Jiahe Qian , Xinkun Wang , Lee A. Cooper , Bo Zhou

Spatial transcriptomics (ST) provides crucial insights into tissue micro-environments, but is limited to its high cost and complexity. As an alternative, predicting gene expression from pathology whole slide images (WSI) is gaining…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Mingcheng Qu , Yuncong Wu , Donglin Di , Yue Gao , Tonghua Su , Yang Song , Lei Fan

Spatial transcriptomics (ST) provides high-resolution pathological images and whole-transcriptomic expression profiles at individual spots across whole-slide scales. This setting makes it an ideal data source to develop multimodal…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Yuxiang Lin , Ling Luo , Ying Chen , Xushi Zhang , Zihui Wang , Wenxian Yang , Mengsha Tong , Rongshan Yu

While spatial transcriptomics (ST) has advanced our understanding of gene expression in tissue context, its high experimental cost limits its large-scale application. Predicting ST from pathology images is a promising, cost-effective…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Zhiceng Shi , Changmiao Wang , Jun Wan , Wenwen Min

Spatial Transcriptomics (ST) is a method that captures gene expression profiles aligned with spatial coordinates. The discrete spatial distribution and the super-high dimensional sequencing results make ST data challenging to be modeled…

Machine Learning · Computer Science 2025-05-08 Qingtian Zhu , Yumin Zheng , Yuling Sang , Yifan Zhan , Ziyan Zhu , Jun Ding , Yinqiang Zheng

Understanding the intricate cellular environment within biological tissues is crucial for uncovering insights into complex biological functions. While single-cell RNA sequencing has significantly enhanced our understanding of cellular…

Image and Video Processing · Electrical Eng. & Systems 2024-11-06 Bingjun Li , Mostafa Karami , Masum Shah Junayed , Sheida Nabavi

Spatial transcriptomics (ST) has emerged as a powerful technology for bridging histology imaging with gene expression profiling. However, its application has been limited by low throughput and the need for specialized experimental…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Tinglin Huang , Tianyu Liu , Mehrtash Babadi , Wengong Jin , Rex Ying

Background: Spatial transcriptomics have emerged as a powerful tool in biomedical research because of its ability to capture both the spatial contexts and abundance of the complete RNA transcript profile in organs of interest. However,…

Genomics · Quantitative Biology 2025-04-18 Shuo Shuo Liu , Shikun Wang , Yuxuan Chen , Anil K. Rustgi , Ming Yuan , Jianhua Hu

For 3D spatial transcriptomics (ST), the high per-section acquisition cost of fully sampling every tissue section remains a significant challenge. Although recent approaches predict gene expression from histology images, these methods…

Image and Video Processing · Electrical Eng. & Systems 2025-07-30 Jiahe Qian , Yaoyu Fang , Xinkun Wang , Lee A. Cooper , Bo Zhou
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