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 ...

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 transcriptomics provides a unique perspective on the genes that cells express and where those cells are located. However, the rapid growth of the technology has come at the cost of ...

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 ...

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 ...

Conventional transcriptomic techniques have revealed much about gene expression at the population and single-cell level—but they overlook one crucial factor: spatial context. In musculoskeletal ...

This article explores how researchers are using spatially resolved methods to explore diverse biological processes from ...

Complete Genomics will share details of various multi-omics and spatial transcriptomics applications based on its sequencing technology at the 2024 American Society of Human Genetics (ASHG) Meeting.

This article explores how single-cell multiomics and spatial transcriptomics are illuminating early pregnancy, uncovering ...

Strapped with an extra APP, people with Down’s syndrome are all but destined to develop Alzheimer’s dementia if they live past middle age. Compared with sporadic forms of the disease, DSAD starts ...