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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 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

Spatial transcriptomics enables gene expression profiling with spatial context, offering unprecedented insights into the tissue microenvironment. However, most computational models treat genes as isolated numerical features, ignoring the…

Machine Learning · Computer Science 2025-11-17 Jiangkai Long , Yanran Zhu , Chang Tang , Kun Sun , Yuanyuan Liu , Xuesong Yan

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 (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

Spatiotemporal gene expression data of the human brain offer insights on the spa- tial and temporal patterns of gene regulation during brain development. Most existing methods for analyzing these data consider spatial and temporal profiles…

Methodology · Statistics 2017-02-27 Tianqi Liu , Ming Yuan , Hongyu Zhao

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…

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

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

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 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

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

The advent of next-generation sequencing-based spatially resolved transcriptomics (SRT) techniques has reshaped genomic studies by enabling high-throughput gene expression profiling while preserving spatial and morphological context.…

Applications · Statistics 2025-02-20 Bencong Zhu , Alberto Cassese , Marina Vannucci , Michele Guindani , Qiwei Li

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

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

Many cellular responses to surrounding cues require temporally concerted transcriptional regulation of multiple genes. In prokaryotic cells, a single-input-module motif with one transcription factor regulating multiple target genes can…

Subcellular Processes · Quantitative Biology 2019-06-19 Jingyu Zhang , Hengyu Chen , Ruoyan Li , David A. Taft , Guang Yao , Fan Bai , Jianhua Xing

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

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

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

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