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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 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 (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

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 (ST) provides spatially resolved measurements of gene expression, enabling characterization of the molecular landscape of human tissue beyond histological assessment as well as localized readouts that can be aligned…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Konstantin Hemker , Andrew H. Song , Cristina Almagro-Pérez , Guillaume Jaume , Sophia J. Wagner , Anurag Vaidya , Nikola Simidjievski , Mateja Jamnik , Faisal Mahmood

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 (ST) technologies enable gene expression profiling with spatial resolution, offering unprecedented insights into tissue organization and disease heterogeneity. However, current analysis methods often struggle with…

Spatially resolved transcriptomics brings exciting breakthroughs to single-cell analysis by providing physical locations along with gene expression. However, as a cost of the extremely high spatial resolution, the cellular level spatial…

Genomics · Quantitative Biology 2024-02-19 Hongzhi Wen , Wenzhuo Tang , Wei Jin , Jiayuan Ding , Renming Liu , Xinnan Dai , Feng Shi , Lulu Shang , Hui Liu , Yuying Xie

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

The development of single-cell and spatial transcriptomics has revolutionized our capacity to investigate cellular properties, functions, and interactions in both cellular and spatial contexts. However, the analysis of single-cell and…

Genomics · Quantitative Biology 2024-12-09 Shuang Ge , Shuqing Sun , Huan Xu , Qiang Cheng , Zhixiang Ren

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) 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…

Deep learning-based nuclei segmentation and classification in pathology images typically rely on large-scale pixel-level manual annotations, which are costly and difficult to obtain across diverse tissues and staining conditions. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Kazuya Nishimura , Ryoma Bise , Haruka Hirose , Yasuhiro Kojima

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 spatially-resolved gene expression, offering crucial insights into tissue architecture and complex diseases. However, its prohibitive cost limits widespread adoption, leading to significant attention on…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Taejin Jeong , Joohyeok Kim , Jinyeong Kim , Chanyoung Kim , Seong Jae Hwang

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

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

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 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) 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
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