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 ...

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.

Scientists at Duke-NUS Medical School have developed two powerful computational tools that could transform how researchers study the "conversations" between cells inside the body. The tools, called ...

Through multiomics—combined genomics, transcriptomics, proteomics, digital pathology, and other technologies yet to fully unfold—we can now obtain a complete dynamic vision of cancer,” argue the ...

Spatial transcriptomics offers a revolutionary approach to understanding the tumor microenvironment (TME) in solid tumors by preserving the spatial context of gene expression, which is crucial for ...

Spatial transcriptomics data from osteosarcoma cells. Left) A spatial map of the transcriptome segmented into individual cells using machine learning, with each dot representing a RNA transcript and ...

“Hey model, if I prompt you with the marker genes for a cell type, can you complete the transcription factors that you believe would be highly expressed with expression of these genes?” posed ...

Immune low-response states significantly impact the effectiveness of immunotherapy in cancer treatment. These states ...