Enables Whole-Transcriptome In Situ Spatial Biology with Single-Cell Sensitivity at ScaleDebuts at AACR Annual Meeting 2026 ...

On March 31, 2026, William Blair upgraded 10x Genomics from “Market Perform” to “Outperform,” highlighting its best-in-class genomics platforms and exposure to growing demand for large-scale ...

Spatial biology is a rapidly advancing discipline that examines biological molecules (such as DNA, RNA, and proteins) within their native locations in tissues. This approach offers critical insight ...

The global initiative aims to profile up to 100,000 patient specimens to scale M-Optimus, the world model of biology, representing a ~20x increase in scale over existing data available in the world ...

Abstract: Spatial transcriptomics (ST) provides spatially resolved gene expression but is often limited by coarse resolution, such as the ~55 μm capture spots of the 10x Visium platform. Computational ...

HONG KONG, Feb. 13, 2026 /PRNewswire/ -- Omics Empower, a global life science service provider specializing in single-cell sequencing and spatial transcriptomics, announced that Xenium™ In Situ ...

HONG KONG, Feb. 13, 2026 /PRNewswire/ — Omics Empower, a global life science service provider specializing in single-cell sequencing and spatial transcriptomics, announced that Xenium™ In Situ Spatial ...

Graph Convolutional Networks (GCNs) are widely applied for spatial domain identification in spatial transcriptomics (ST), where node representations are learned by aggregating information from ...

With a trio of partnership announcements this month, 10x Genomics has signaled it is looking beyond its traditional focus on research tools for academic, government, and industry customers, by ...

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, ...

Lymph nodes are key sites of adaptive immune responses, yet how immune cells coordinate their activities in space and time remains poorly understood. We combined high-resolution spatial ...