As the “Method of the Year 2024”, spatial proteomics (SP) enables in situ characterization of protein localization, abundance ...

Using single-cell sequencing and spatial tools, researchers have created the most comprehensive map of the maternal–fetal interface yet.

New spatial transcriptomics approach combined with machine learning maps gene expression across whole mouse body sections, ...

Jasmine Plummer shares the spatial omics techniques she has developed to investigate the cellular processes underlying ...

Adelaide University is leading the international Wheat Spatial Omics Consortium (WSOC) of more than 30 institutions in nine countries, which will explore how collaborative research in spatial omics ...

Type 1 diabetes researchers have made great progress in understanding the disease in the last two decades, even as a cure remains elusive. Now they have something that benefits any scientific effort.

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 ...

A large-scale effort to map epigenetic changes in the aging brain is offering an unprecedented view into how molecular processes evolve over time. By integrating multiple layers of genomic and spatial ...

ChatSpatial replaces ad-hoc LLM code generation with schema-enforced orchestration — the LLM selects methods and parameters from a curated registry instead of writing arbitrary code, ensuring ...

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy characterized by marked cellular and spatial diversity within the tumor microenvironment (TME). The transforming growth factor-β ...

Here, we present Randomized Spatial PCA (RASP), a novel spatially aware dimensionality reduction method for spatial transcriptomics (ST) data. RASP is designed to be orders-of-magnitude faster than ...