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 ...
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 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 ...
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 ...
Association of tumor extracellular matrix density with recurrence in invasive lobular carcinoma. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not include a ...
Why do so many promising drugs fail? This article explores how spatial multiomics reveals hidden cell interactions, helping ...
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 ...
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