A team of Vanderbilt researchers has released a new benchmarking study that aims to assist scientists in selecting the most effective methods for analyzing spatial transcriptomics (ST) data. ST ...

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 ...

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.

Technological advances in sequencing have fueled the “omics revolution,” making big data a staple of biological research. However, many researchers feel ill-equipped to wrangle and analyze these ...

A new study in Science Bulletin presents DVSTP, a deep learning system that integrates pathology images with spatial ...

Transcriptomics is the study of the transcriptome, which is the complete set of RNA transcripts produced by the genome at a specific time or under particular conditions. It involves the analysis of ...

Researchers developed a new computational method to analyze complex tissue data that could transform our current understanding of diseases and how we treat them. Researchers at the University of ...

New simulator and computational tools generate realistic ‘virtual tissues’ and map cell-to-cell ‘conversations’ from spatial transcriptomics data, potentially accelerating AI-driven discoveries in ...

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 ...

Researchers at the University of Michigan and Brown University have developed a new computational method to analyze complex tissue data that could transform our current understanding of diseases and ...