Multimodal contrastive learning for spatial gene expression prediction using histology images
In recent years, the advent of spatial transcriptomics (ST) technology has unlocked
unprecedented opportunities for delving into the complexities of gene expression patterns …
unprecedented opportunities for delving into the complexities of gene expression patterns …
Hest-1k: A dataset for spatial transcriptomics and histology image analysis
Spatial transcriptomics enables interrogating the molecular composition of tissue with ever-
increasing resolution and sensitivity. However, costs, rapidly evolving technology, and lack …
increasing resolution and sensitivity. However, costs, rapidly evolving technology, and lack …
Transcriptomics-guided slide representation learning in computational pathology
G Jaume, L Oldenburg, A Vaidya… - Proceedings of the …, 2024 - openaccess.thecvf.com
Self-supervised learning (SSL) has been successful in building patch embeddings of small
histology images (eg 224 x 224 pixels) but scaling these models to learn slide embeddings …
histology images (eg 224 x 224 pixels) but scaling these models to learn slide embeddings …
What makes for good morphology representations for spatial omics?
Spatial omics has transformed our understanding of tissue architecture by preserving spatial
context of gene expression patterns. Simultaneously, advances in imaging AI have enabled …
context of gene expression patterns. Simultaneously, advances in imaging AI have enabled …
Gene expression prediction from histology images via hypergraph neural networks
Spatial transcriptomics reveals the spatial distribution of genes in complex tissues, providing
crucial insights into biological processes, disease mechanisms, and drug development. The …
crucial insights into biological processes, disease mechanisms, and drug development. The …
Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location, and histology using GCN
S Xue, F Zhu, J Chen, W Min - Briefings in Bioinformatics, 2025 - academic.oup.com
Spatial transcriptomics (ST technology allows for the detection of cellular transcriptome
information while preserving the spatial location of cells. This capability enables researchers …
information while preserving the spatial location of cells. This capability enables researchers …
Innovative super-resolution in spatial transcriptomics: a transformer model exploiting histology images and spatial gene expression
Spatial transcriptomics technologies have shed light on the complexities of tissue structures
by accurately mapping spatial microenvironments. Nonetheless, a myriad of methods …
by accurately mapping spatial microenvironments. Nonetheless, a myriad of methods …
An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue …
The application of deep learning to spatial transcriptomics (ST) can reveal relationships
between gene expression and tissue architecture. Prior work has demonstrated that inferring …
between gene expression and tissue architecture. Prior work has demonstrated that inferring …
Molecular connectomics: Placing cells into morphological tissue context
Molecular connectomics: Placing cells into morphological tissue context | PLOS Biology Skip to
main content Advertisement PLOS Biology Browse Current Issue Journal Archive Collections …
main content Advertisement PLOS Biology Browse Current Issue Journal Archive Collections …
Towards Unified Molecule-Enhanced Pathology Image Representation Learning via Integrating Spatial Transcriptomics
Recent advancements in multimodal pre-training models have significantly advanced
computational pathology. However, current approaches predominantly rely on visual …
computational pathology. However, current approaches predominantly rely on visual …