Spatial transcriptomics and gene expression analysis represent a transformative approach in biomedical research, integrating the spatial context of tissues with high-resolution profiling of gene ...

Biological tissues are made up of different cell types arranged in specific patterns, which are essential to their proper functioning. Understanding these spatial arrangements is important when ...

This figure shows how the STAIG framework can successfully identify spatial domains by integrating image processing and contrastive learning to analyze spatial transcriptomics data effectively.

The human lymphatic system is notoriously difficult to map due to its size and variability among individuals. Spatial ...

Knowing the location of a gene within intact tissue or a single cell allows scientists to unlock unknown cellular functions. This information is often lost in most genetic sequencing techniques, but ...

Researchers at the Max Delbrück Center have developed an open-source spatial transcriptomics (ST) platform, called Open-ST, that creates 3D molecular maps from patient tissue samples with subcellular ...

Researchers developed a new computational method to analyze complex tissue data that could transform our current understanding of diseases and how we treat them. Researchers at the University of ...

Neurodegenerative diseases affect more than 57 million people globally. The incidence of these diseases, from Alzheimer's to Parkinson's to ALS and beyond, is expected to double every 20 years. Though ...

In this GEN Learning Lab, our expert panelists Linda Orzolek, MS, MB, Xuhuai Ji, MD, PhD, and Christina Chang, PhD, will discuss the current landscape of imaging- and next-generation sequencing-based ...

A recent integrative analysis of single-cell sequencing and single-cell spatial mapping of lymph node metastasis in breast cancer reveals novel mechanisms of the metabolic-immune interaction that ...