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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

Spatial transcriptomics (ST) is a novel technique that simultaneously captures pathological images and gene expression profiling with spatial coordinates. Since ST is closely related to pathological features such as disease subtypes, it may…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Kazuya Nishimura , Ryoma Bise , Yasuhiro Kojima

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

With the rapid advancement of Spatial Resolved Transcriptomics (SRT) technology, it is now possible to comprehensively measure gene transcription while preserving the spatial context of tissues. Spatial domain identification and gene…

Genomics · Quantitative Biology 2024-08-14 Donghai Fang , Fangfang Zhu , Dongting Xie , Wenwen Min

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

Spatial transcriptomics (ST) enables mapping gene expression with spatial context but is severely affected by high sparsity and technical noise, which conceals true biological signals and hinders downstream analyses. To address these…

Machine Learning · Computer Science 2026-03-10 Sayeem Bin Zaman , Fahim Hafiz , Riasat Azim

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 provides an unprecedented perspective for deciphering tissue spatial heterogeneity. However, high-resolution spatial transcriptomic technology remains constrained by limited gene coverage, technical complexity, and…

Biomolecules · Quantitative Biology 2026-05-19 Xinlei Huang , Weihao Dai , Zijun Qin , Xin Yu , Di Wang , Yanran Liu , Lixin Cheng , Xubin Zheng

Spatial transcriptomics is an emerging field that enables the identification of functional regions based on the spatial distribution of gene expression. Integrating this functional information present in transcriptomic data with structural…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Shanaka Liyanaarachchi , Chathurya Wijethunga , Shihab Aaqil Ahamed , Akthas Absar , Ranga Rodrigo

Spatially Resolved Transcriptomics (SRT) is a cutting-edge technique that captures the spatial context of cells within tissues, enabling the study of complex biological networks. Recent graph-based methods leverage both gene expression and…

Machine Learning · Computer Science 2025-06-24 Yunhak Oh , Junseok Lee , Yeongmin Kim , Sangwoo Seo , Namkyeong Lee , Chanyoung Park

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 (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

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

We present an approach to denoising spatial transcriptomics images that is particularly effective for uncovering cell identities in the regime of ultra-low sequencing depths, and also allows for interpolation of gene expression. The method…

Spatially resolved transcriptomics (SRT) has evolved rapidly through various technologies, enabling scientists to investigate both morphological contexts and gene expression profiling at single-cell resolution in parallel. SRT data are…

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) measures mRNA expression while preserving spatial organization, but multi-slice analysis faces two coupled difficulties: large non-rigid deformations across slices and inter-slice batch effects when alignment…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Bonian Han , Cong Qi , Przemyslaw Musialski , Zhi Wei

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

Recent advancements in Spatial Transcriptomics (ST) technology have facilitated detailed gene expression analysis within tissue contexts. However, the high costs and methodological limitations of ST necessitate a more robust predictive…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Youngmin Chung , Ji Hun Ha , Kyeong Chan Im , Joo Sang Lee

Cellular identity and function are linked to both their intrinsic genomic makeup and extrinsic spatial context within the tissue microenvironment. Spatial transcriptomics (ST) offers an unprecedented opportunity to study this, providing in…

Machine Learning · Computer Science 2026-02-16 Rui Yan , Xiaohan Xing , Xun Wang , Zixia Zhou , Md Tauhidul Islam , Lei Xing