Spatial Transcriptomics

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6 papers in the last four weeks, with none the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

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GATE-ST: Gene-Aware Text-image Encoder for Spatial Transcriptomics
Sep 30, 2026Lucas Ni, Jian Luo, Wentao Huang +1Spatial Transcriptomics Multimodal Embedding
Ridge High School Basking Ridge, United States · Stony Brook University Stony Brook, United States
Towards Scalable Context-Aware Single-Cell Spatial Transcriptomics Prediction from Histology Images
Sep 29, 2026Zijun Gao, Chunbin Gu, Jinxi Xiang +2Spatial Transcriptomics Spatial Gene Expression Prediction
The Chinese University of Hong Kong · Stanford University School of Medicine
Preserving DEG Rankings for Gene Discovery in Histology-Based Spatial Gene Expression Prediction
Sep 27, 2026Kaito Shiku, Kazuya Nishimura, Yasuhiro Kojima +1Spatial Transcriptomics Learning to Rank
Kyushu University, Japan · The University of Osaka, Japan · National Cancer Center, Japan
SpaFactor: Lightweight Spatial Context-Aware Gene Program Modeling for Histology-to-Transcriptomics Inference
Sep 23, 2026Shiting Ruan, Xitong Ling, Qiming He +6Computational Pathology Spatial Transcriptomics
Shenzhen International Graduate School, Tsinghua University, Shenzhen, China · Fuzhou University, Fuzhou, Fujian, China · Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China +1
Benchmarking Active Spot Selection for Cost-Efficient Spatial Transcriptomics
Sep 23, 2026Zheyu Zhu, Junchao Zhu, Fengbei Liu +7Spatial Transcriptomics Active Learning
University of Pennsylvania, Philadelphia, PA 19104, USA · Vanderbilt University, Nashville, TN, USA · Cornell Tech, New York, NY 10044, USA +4
Hyperbolic Contrastive Learning with Entailment for Spatial Transcriptomics
Sep 14, 2026Daniela Vega, Paula Cárdenas, Hannah Ceballos +2Contrastive Learning Spatial Transcriptomics
Center for Research and Formation in Artificial Intelligence Universidad de los Andes, Colombia
VOICE: A Vision-Omics Foundation Model Integrating Direct and Retrieval-Based Prediction of In-situ Single-Cell Gene Expression
Aug 8, 2026Xin Luo, Yicheng Tao, Haoxuan Zeng +6Computational Pathology Spatial Transcriptomics
University of Michigan Ann Arbor, Michigan, USA · Weill Cornell Medicine New York, New York, USA
CellWorld: From Gene-Level Reconstruction to Latent Cell Prediction in Spatial Transcriptomics Foundation Models
Aug 7, 2026Haiping Liu, Qian Zhao, Lijing Lin +2Spatial Transcriptomics Self-Supervised Pre-Training
University of Manchester
Gene Ontology-Guided Hierarchical Spatial Gene Expression Prediction from Histopathology Images
Aug 1, 2026Zhiwen Xu, Xiaoming Yan, Chengkun Wu +3Computational Pathology Spatial Transcriptomics
National University of Defense Technology Changsha, China
HistoGPA: A Context-Conditioned Gene-Prior Attention Framework for Histology-Based Spatial Gene Expression Prediction
Jul 27, 2026Ziang Liu, Xinhai Chen, Yigui Feng +3Computational Pathology Spatial Transcriptomics
Laboratory of Digitizing Software for Frontier Equipment, National University of Defense Technology · National Key Laboratory of Parallel and Distributed Computing, National University of Defense Technology · College of Computer Science and Technology, National University of Defense Technology, Changsha 410073, China
HierarchicalDAEW: Domain-Aware Edge-Weighted Graph Convolution with Evidential Uncertainty for Multi-Section Spatial Gene Expression Prediction from H&E Histology
Jul 23, 2026Kritanu Chattopadhyay, Soumya Chatterjee, Ondrej Krejcar +1Computational Pathology Spatial Transcriptomics
Department of Mechanical Engineering, National Institute of Technology Durgapur,, Durgapur, 713209, West Bengal, India · Department of Electrical Engineering, National Institute of Technology Durgapur,, Durgapur, 713209, West Bengal, India · Research Center, Skoda Auto University, Na Karmeli 1457, Mlada Boleslav, 293 01,, Czech Republic +1
LATTICE: Graph Self-Supervised Learning for Multimodal Spatial Omics Integration
Jul 15, 2026Jagan Mohan Reddy Dwarampudi, Veena Kochat, Suresh Satpati +2Spatial Transcriptomics Graph SSL
University of Houston · MD Anderson Cancer Center
COAST: Context-Aware Differential Learning for Gene Expression Prediction in Spatial Transcriptomics
Jul 10, 2026Keunho Byeon, Sunhong Park, Jeewoo Lim +1Spatial Transcriptomics Spatial Gene Expression Prediction
School of Electrical Engineering, Korea University, Seoul 02841, Republic of Korea
SpaCellAgent: A Self-Evolving LLM-Based Multi-Agent Framework for Trajectory Analysis
Jul 8, 2026Songhan Wang, Haoang Chi, He Li +6Spatial Transcriptomics LLM Agent Orchestration
University of Shanghai for Science and Technology · National University of Defense Technology · Hong Kong Baptist University +3
DriftST: One-Step Generative Inference of Spatial Transcriptomics from H&E Histology
Jul 6, 2026Yuhang Yang, Yonggan Bu, Shengyuan Zhou +2Computational Pathology Spatial Transcriptomics
University of Science and Technology of China, Hefei, China · Peking University Cancer Hospital, Beijing, China
JASPR: Joint Spatial Representation learning of histology and spatial genomics for improved virtual genomic screening and clinical prognostication
Jun 24, 2026Marija Pizurica, Eric Zimmermann, Neil Tenenholtz +5Cancer Genomics Computational Pathology
Microsoft Research, Cambridge, MA, United States · Stanford University, CA, United States
Contrastive and Adaptive Multi-modal Masked Autoencoder for Spatial Transcriptomics
Jun 19, 2026Joohyeok Kim, Taejin Jeong, Jinyeong Kim +1Computational Pathology Spatial Transcriptomics
Department of Artificial Intelligence, Yonsei University, Seoul, Republic of Korea · Department of Computer Science, Yonsei University, Seoul, Republic of Korea · Yonsei University College of Medicine, Seoul, Republic of Korea
HiST: A Hierarchical Sparse Transformer for Cross-Modal Spatial Transcriptomics Modeling
Jun 12, 2026Weiyi Wu, Xinwen Xu, Xingjian Diao +4Computational Pathology Spatial Transcriptomics
Dartmouth College · Mass General Hospital · New Jersey Institute of Technology +1
SNR-ST-Mix: Sample-specific Neighborhood Regression Mixup for Augmented Spatial Transcriptomics Imputation with Deep Neural Network
Jun 7, 2026Hongyi Yu, Yaoyu Fang, Jiahe Qian +3Synthetic Data Augmentation Spatial Transcriptomics
Northwestern University, Department of Radiology, Chicago, IL, USA · Yale University, Department of Biostatistics, New Haven, CT, USA · Northwestern University, Department of Cell and Developmental Biology, Chicago, IL, USA +1
Querying Counterfactuals on Tissue Graphs with Supervised Disentanglement
Jun 7, 2026Abdul Moeed, Stefan Schrod, Martin Rohbeck +4Spatial Transcriptomics Disentangled Representation Learning
Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany · Helmholtz Information & Data Science School for Health, Germany · Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany +4
Single-Cell Cross-Modal Transfer by Adversarial Fine-Tuning of Foundation Models
Jun 4, 2026Joseph Boyd, Matthew Lyon, Martino Mansoldo +2Spatial Transcriptomics Fine-Tuning
GSK.ai, GlaxoSmithKline, London, United Kingdom.
GC-MoE: Genomics-Guided Cell-Type-Specific Mixture of Experts for Histology-Based Single-Cell Spatial Transcriptomics
Jun 1, 2026Kaito Shiku, Ahtisham Fazeel Abbasi, Ryoma Bise +4Computational Pathology Spatial Transcriptomics
Kyushu University, Japan · German Research Center for Artificial Intelligence (DFKI GmbH), Germany · RPTU University Kaiserslautern-Landau, Germany +3
CodeCytos: AI-assisted spatial molecular imaging analysis via code-augmented agent action space
May 30, 2026Hung Q. Vo, Huy Q. Vo, Son T. Ly +6Computational Pathology Spatial Transcriptomics
University of Houston, Department of Electrical and Computer Engineering, Houston, Texas, 77004, USA · Houston Methodist Hospital, Department of Systems Medicine and Biomedical Engineering, Houston, Texas, 77030, USA
Spatial Transcriptomics-Guided Alignment Enhances Molecular Profiling in Pathology Foundation Model
May 29, 2026Fengtao Zhou, Yingxue Xu, Zhengyu Zhang +20Spatial Transcriptomics Cross-Modal Alignment
Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China · Department of Pathology, Nanfang Hospital, Southern Medical University, Guangzhou, China · Department of Pathology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China +16
Geometry-First Generative Spatial Single-Cell Reconstruction
May 27, 2026Ehtesamul Azim, Muhtasim Noor Alif, Tae Hyun Hwang +2Spatial Transcriptomics Genomics
University of Central Florida Orlando, Florida, USA · Vanderbilt University Medical Center Nashville, Tennessee, USA · Arizona State University Tempe, Arizona, USA
Verifiable Benchmarking of Long-Horizon Spatial Biology
May 27, 2026Ian Diks, Harihara Muralidharan, Tim Proctor +1Spatial Transcriptomics Benchmark Design
LatchBio, San Francisco, CA, USA
FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction
May 18, 2026Qi Si, Penglei Wang, Yushuai Wu +5Spatial Transcriptomics Spatial Gene Expression Prediction
Shanghai Academy of Artificial Intelligence for Science, Shanghai, China. · School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. · Artificial Intelligence Innovation and Incubation Institute, Fudan University, Shanghai, China.
DUET: Dual-Paradigm Adaptive Expert Triage with Single-cell Inductive Prior for Spatial Transcriptomics Prediction
May 13, 2026Junchao Zhu, Ruining Deng, Junlin Guo +11Spatial Transcriptomics Spatial Gene Expression Prediction
Vanderbilt University, Tennessee, USA · Weill Cornell Medicine, New York, USA · Vanderbilt University Medical Center, Tennessee, USA
HEXST: Hexagonal Shifted-Window Transformer for Spatial Transcriptomics Gene Expression Prediction
May 6, 2026Keunho Byeon, Jin Tae KwakComputational Pathology Spatial Transcriptomics
School of Electrical Engineering, Korea University, Seoul
CHRep: Cross-modal Histology Representation and Post-hoc Calibration for Spatial Gene Expression Prediction
Apr 23, 2026Changfan Wang, Xinran Wang, Donghai Liu +4Spatial Transcriptomics Post-Hoc Calibration
Beijing University of Posts and Telecommunications, Beijing 100876, China, and also with the Beijing Key Laboratory of Network System and Network Culture, Beijing 100876, China · Peking University Third Hospital, Beijing 100191, China

Sep 30, 2026, cs.AIJ/K move · Enter open · S save

GATE-ST: Gene-Aware Text-image Encoder for Spatial Transcriptomics

Lucas Ni, Jian Luo, Wentao Huang, Chao Chen

Ridge High School Basking Ridge, United States · Stony Brook University Stony Brook, United States

Spatial Transcriptomics Multimodal Embedding Spatial Gene Expression Prediction Gene Expression Prediction from Histopathology Images Whole-Slide Image Analysis

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Spatial transcriptomics enables spatially resolved gene expression analysis from slide-level images while preserving morphological features, providing valuable information for studying disease mechanisms and developing treatments. However, spatial gene expression profiling typically requires expensive and time-consuming tests. While existing image-based prediction optimizations mostly revolve around including positional embeddings and further image-based changes, text-based optimizations remain relatively unexplored. We present GATE-ST, which incorporates text-based inputs into image-based spatial gene expression predictions. With this approach, generated text descriptions of genes are utilized to better spatial transcriptomics prediction results. Gene summaries are put through a text encoder, generating embeddings that integrate with image embeddings through cross-attention layers to align with morphological features. We demonstrate the effectiveness of such text inputs by benchmarking performance against random gene embeddings and multiple other image-text fusion architectures, and show that GATE-ST outperforms these alternatives. Our results demonstrate the effectiveness of GATE-ST in pathology imaging, which may greatly reduce the time and cost of accurate spatial transcriptomic predictions, proving the potential of text-guided spatial gene expression prediction.

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Latest papers 32