MGI Tech Co., Ltd. (MGI), a company committed to developing core tools and technologies that drive innovation in life sciences, today launched Go Spatial in Europe and welcomed Omics Empower GmbH as a ...

A new multiplex immunofluorescence workflow using standard laboratory equipment and open-source software enables detailed ...

The heart and brain are among the earliest and most metabolically demanding organs in human development. Though historically studied in isolation, both ...

Researchers at The University of Texas MD Anderson Cancer Center have developed a spatial map of muscle-invasive bladder cancer, revealing how tumor cell states, immune environments and therapeutic ...

A novel spatial transcriptomics atlas developed by Northwestern Medicine scientists may improve the understanding of niche cellular interactions in the gastrointestinal tract that promote the ...

In this post, we will show you how to enable or disable Spatial Sound in Windows 11. Spatial Sound is an advanced audio feature that creates an immersive, 3D sound experience, without requiring ...

Abstract: Spatial transcriptomics technology enables researchers to acquire both spatial location information and gene expression data within tissues, providing new perspectives for understanding ...

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 ...

The rapid development of spatial transcriptomics (ST) technologies has greatly advanced the understanding of gene expression, tissue architecture, cellular composition, and disease mechanisms within ...

The liver is a highly multifunctional organ that can perform many metabolic and immunological functions due to a highly complex spatially organised microarchitecture that is disturbed in many liver ...

Artificial intelligence (AI) has become a common tool for bioinformatics, with hundreds of methods published in recent years. Due to the training data demands of deep-learning algorithms, ...