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 ...

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 ...

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 ...

IDH-mutant glioma, caused by abnormalities in a specific gene (IDH), is the most common malignant brain tumor among young adults under the age of 50. It is a refractory brain cancer that is difficult ...

Gene regulation in plants is orchestrated through a multilayered network of molecular mechanisms encompassing chromatin organization, transcriptional control, RNA processing, RNA modification, and ...

Modern machine learning approaches have shown remarkable success in extracting patterns from high-dimensional biological data. However, when applied to spatial transcriptomics, these methods face ...

The evolution of single-cell sequencing and spatial omics technologies has revolutionised our ability to study tissues and diseases with unprecedented resolution. It has long been recognised that gene ...

The Asian honeybee (Apis cerana) is one of the primary bee species widely cultivated in East Asia, with a rich beekeeping tradition in China, Japan, and India, contributing significantly to the ...

Biological systems are inherently three-dimensional—tissues form intricate layers, networks, and architectures where cells interact in ways that extend far beyond a flat plane. To capture the true ...

Spatial transcriptomics enables researchers to measure gene expression in tissue sections while preserving their spatial organisation. Unlike traditional RNA sequencing, which requires dissociating ...