Blog

Spatial transcriptomics has evolved from a technology-selection problem into a study-design problem. After choosing a spatial modality—sequencing- or imaging-based—a second, equally important question remains: How broadly should you measure the transcriptome? Should you profile every detectable transcript for unbiased discovery, or focus on a carefully selected panel for greater Read More

Understanding where genes are expressed within tissues can be just as important as knowing which genes are expressed. Tissue development, immune responses, and disease progression all depend on the spatial organization of cells. Traditional single-cell RNA sequencing captures gene expression but requires tissue dissociation, losing that spatial context. Spatial transcriptomics addresses Read More

The Next Bottleneck in Spatial Biology Isn’t Data Generation Spatial omics technologies such as Visium, Xenium, CosMx, and multiplexed imaging platforms such as PhenoCycler have transformed how researchers study tissues by enabling molecular measurements within their native spatial context. These technologies now routinely generate: For most Read More

The nature of biological research has fundamentally shifted. We are no longer limited by a lack of data, but by our ability to make sense of it. Today, a single single-cell RNA sequencing experiment can generate millions of data points, mapping the precise molecular state of thousands of individual Read More

Why standard spatial analysis misses key tumor behavior Spatial transcriptomics has enabled researchers to map gene expression within intact tissue architecture, providing a major step forward in understanding tumor organization1. However, most current analytical workflows still struggle to fully resolve functional tumor heterogeneity. The limitation is not spatial Read More

About BioTuring Our bioinformatics startup empowers the next generation of scientists and innovators to turn data into breakthroughs. By combining biology, AI, and advanced analytics, we build tools that help researchers, students, and global pharmaceutical teams uncover hidden insights, accelerate drug discovery, and develop smarter, more precise treatments. Our Read More

Abstract Gene Set Enrichment Analysis (GSEA) is a widely adopted method for pathway-level interpretation of transcriptomic data. In the canonical formulation of Subramanian et al. [3], statistical significance is estimated through thousands of phenotype permutations—a procedure that becomes computationally prohibitive for large gene sets and comprehensive pathway Read More

Spatial transcriptomics has expanded our ability to identify cell types within tissues. However, understanding tumor biology requires more than composition alone. This article builds on findings from Takano et al. (Nature Communications, 2024) to examine how spatial organization, including gradients and compartmentalization, shapes interpretation of tumor systems. Read More

About our B-GENS – BioTuring Trainee Program 2026 BioTuring is an innovative bioinformatics company that develops algorithms, and agentic AI software to serve scientists from hundreds of pharmaceutical companies and leading research institutions, enabling discoveries about human diseases. Our biennial program helps you advance in frontier HPC (high Read More

SAN DIEGO, Calif. — January 26, 2026 — BioTuring and 10x Genomics, Inc. (Nasdaq: TXG), a leader in single cell and spatial biology, today announced a strategic collaboration to streamline and accelerate the path from data generation to biological insight for single cell and spatial research workflows. Read More