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.

Enhancing a low-cost, minimally invasive screening test for dihydropyrimidine dehydrogenase mutations linked to 5-fluorouracil sensitivity by integrating computational mutation predictions. This is an ...

Spatial transcriptomics (ST) technologies reveal the spatial organization of gene expression in tissues, providing critical insights into development, neurobiology, and cancer. However, the high cost ...

A team of researchers has constructed the most detailed single-cell map of the adult human prostate to date, cataloging more ...

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 ...

Andreas Pfenning discusses the techniques being developed and used to study neuronal heterogeneity and the therapeutic potential of his work.

Neoadjuvant immunotherapy in combination with chemotherapy in resectable locally advanced head and neck squamous cell carcinoma: A randomized, open label, phase II clinical trial. This is an ASCO ...

Tumors contain many different types of cells organized in complex spatial patterns that can influence how the disease progresses. Because of this, it is hard to predict how a tumor will develop and ...