Researchers from Harbin Medical University have developed a powerful new resource called So3D that helps scientists explore how cells are organized and interact within three-dimensional tissues. Traditional biological studies often rely on two-dimensional data, which can overlook the complex structures that make up real tissues and organs. Understanding how cells function in 3D space is crucial for revealing how they communicate, organize, and contribute to health or disease.

Graphical Abstract

The So3D database brings together an impressive collection of 3D spatial transcriptomics data, combining 72 datasets and over one million spatial points from multiple species. It also integrates reference RNA sequencing data from more than 760,000 individual cells. So3D allows researchers to analyze how genes are expressed within specific 3D regions of tissue, visualize cell types and interactions, and study biological pathways within realistic spatial contexts. By mapping tissues in three dimensions, So3D provides an essential tool for investigating tissue microenvironments, identifying biomarkers, and understanding how diseases develop at the cellular level.

Availability – http://bio-bigdata.hrbmu.edu.cn/So3D or https://so3d.bio-database.com/

Zhao H, Yin X, Wang S, Geng Z, Yu W, Yu H, Ning S, Wang L. (2025) So3D, a comprehensive three-dimensional spatial omics resource for decoding tissue architecture in physiology and disease. Nucleic Acids Research 53(10): gkaf998. [article]

Researchers from Harbin Medical University have developed a powerful new resource called So3D that helps scientists explore how cells are organized and interact within three-dimensional tissues. Traditional biological studies often rely on two-dimensional data, which can overlook the complex structures that make up real tissues and organs. Understanding how cells function in 3D space is crucial for revealing how they communicate, organize, and contribute to health or disease.

Graphical Abstract

The So3D database brings together an impressive collection of 3D spatial transcriptomics data, combining 72 datasets and over one million spatial points from multiple species. It also integrates reference RNA sequencing data from more than 760,000 individual cells. So3D allows researchers to analyze how genes are expressed within specific 3D regions of tissue, visualize cell types and interactions, and study biological pathways within realistic spatial contexts. By mapping tissues in three dimensions, So3D provides an essential tool for investigating tissue microenvironments, identifying biomarkers, and understanding how diseases develop at the cellular level.

Availability – http://bio-bigdata.hrbmu.edu.cn/So3D or https://so3d.bio-database.com/

Zhao H, Yin X, Wang S, Geng Z, Yu W, Yu H, Ning S, Wang L. (2025) So3D, a comprehensive three-dimensional spatial omics resource for decoding tissue architecture in physiology and disease. Nucleic Acids Research 53(10): gkaf998. [article]

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