GitHub

Predicting spatial transcriptomics from H&E images

This repository contains the code of the paper "DeepSpot: Leveraging Spatial Context for Enhanced Spatial Transcriptomics Prediction from H&E Images". Authors: Kalin Nonchev, Sebastian Dawo, Karina ...
Phys.org

Software tool can detect hidden errors in complex tissue analyses

A new software tool, ovrlpy, improves quality control in spatial transcriptomics, a key technology in biomedical research. Developed by the Berlin Institute of Health at Charité (BIH) in international ...
ahajournals.org

Single-Cell Transcriptomics and Lineage Tracing Unveil Parallels in Lymphatic Muscle and Venous Smooth Muscle Development, Identity, and Function

Lymphatic muscle cells (LMCs) are indispensable for lymphatic vessel contraction, and their aberrant recruitment or absence is associated with both primary and secondary lymphedema. Despite their ...
IEEE

Cluster-guided contrastive learning with masked autoencoder for spatial domain identification based on spatial transcriptomics

Abstract: Recent advancements in spatial transcriptomics technology have enabled the capture of gene expression profiles while maintaining spatial information. Accurately identifying spatial ...
GitHub

DeepSpot: Leveraging Spatial Context for Enhanced Spatial Transcriptomics Prediction from H&E Images

Do you want to generate spatial transcriptomics data using your H&E images? We introduce DeepSpot, a novel deep-learning model that predicts spatial transcriptomics from H&E images. DeepSpot employs a ...
BioTechniques

Innovative new tools map cell communication from spatial transcriptomics data

New simulator and computational tools generate realistic ‘virtual tissues’ and map cell-to-cell ‘conversations’ from spatial transcriptomics data, potentially accelerating AI-driven discoveries in ...
eLife

Single-cell transcriptomics identifies altered neutrophil dynamics and accentuated T-cell cytotoxicity in tobacco-flavored e-cigarette-exposed mouse lungs

This manuscript by Kaur et al. identifies differential gene expression in distinct cell populations, specifically myeloid and lymphoid cells, following short-term exposure to e-cigarette aerosols with ...
The Lancet

Spatial transcriptomics uncovers lipid metabolic dysregulation driving immune-stroma crosstalk in Sjögren's Disease

aDivision of Rheumatology, Department of Internal Medicine, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, 510630, China bDepartment of Endocrinology and Metabolism, ...
IEEE

UPSST: Unsupervised Pathology Domain Identification by Integrating Tissue Morphology, Imputing and Clustering of Spatial Transcriptomics With GAT

Abstract: Spatial transcriptomics is an emerging technology that allows for analysis of cellular and molecular heterogeneity at spatial resolution. The accurate identification of pathological regions ...
EurekAlert!

New review decodes transcriptomics: bulk vs. single-cell RNA sequencing

A comprehensive review article titled “Bioinformatics perspectives on transcriptomics: A comprehensive review of bulk and single-cell RNA sequencing analyses,” published in Quantitative Biology, ...
gut.bmj

Dynamic urinary proteomics integrates single-cell and spatial transcriptomics to reveal tumour microenvironment and predict immunotherapy response in biliary tract cancer

Background Most patients with biliary tract cancer (BTC) do not derive durable clinical benefit (DCB) from immune checkpoint inhibitors (ICIs), underscoring the urgent need for predictive biomarkers.
BioWorld

Transcriptomics and AI for drug discovery by reading cell states

A technology that combines transcriptomic data and AI enables a novel approach to drug discovery based on the state of cells, how they behave and which genes they express. The Drugreflector model, ...