Andreas Pfenning discusses the techniques being developed and used to study neuronal heterogeneity and the therapeutic potential of his work.

Many biological functions and systems are influenced by how gene expression is spatially distributed, from subcellular through to tissue, organ, or at embryonic level. Our understanding of these ...

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.

Spatial biology captures molecular complexity by preserving the physical context of cells in their native environments. From deciphering RNA dynamics within stress granules to scaling molecular ...

Spatial transcriptomics (ST) emerges as a pivotal technique for cataloging gene expression across tissue sections while retaining crucial locational data. Traditional methodologies, encompassing bulk ...

Applying single-cell RNA sequencing has led researchers to be able to profile the entire transcriptome of cells. However, these transcriptomes prove difficult to link back to their original location ...

Illumina is raising the curtain on its upcoming entry into spatial transcriptomics, with tech designed to help researchers explore cellular behavior mapped across complex tissues. The announcement ...

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 ...

Tumors contain many different types of cells organized in complex spatial patterns that can influence how the disease progresses. Because of this, it is hard to predict how a tumor will develop and ...

To study biological processes, scientists often take snapshots of the molecules in cells, such as proteins and nucleotides, at specific points in time. In spatial biology, they can leverage molecular ...