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.

Spatial ribonucleic acid (RNA) transcriptomics measures gene expression while preserving each molecule’s coordinates in intact tissue, tying transcripts to histology and local microenvironments.

Co-first author Jiyuan Yang, PhD, St. Jude Department of Computational Biology and co-senior and corresponding author Jiyang Yu, PhD, St. Jude Department of Computational Biology interim chair look at ...

Technological development is key to improving the way hematologic cancer is diagnosed and treated. With this vision, the Josep Carreras Leukemia Research Institute is committed to the creation and ...

Vizgen, Inc., a spatial multi-omics innovator accelerating biological discovery and new drug development, today announced that it will present new spatial multi-omics data at the Society for ...