Blake Rushing, PhD, has launched an independent research laboratory at the UNC Nutrition Research Institute, advancing ...
DeepSpot: Leveraging Spatial Context for Enhanced Spatial Transcriptomics Prediction from H&E Images
Do you want to generate spatial transcriptomics data using your H&E images? We introduce DeepSpot, a novel deep-learning model that predicts spatial transcriptomics from H&E images. DeepSpot employs a ...
The global spatial biology market is projected to grow at a compound annual growth rate (CAGR) of approximately 15% over the ...
The market is fueled by the technology’s ability to map biomolecules and cellular interactions within tissues, enabling ...
The rapid advancements and decreasing cost of omics technologies such as genomics, epigenomics, transcriptomics, proteomics, ...
Disease microbiology is a vast field of research, especially encompassing the recent and rapid advancements of omics science ...
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 ...
The preprint is available here. DeepSpot2Cell predicts virtual single-cell spatial transcriptomics as follows: (1) During training, the model takes as input (i) the cropped cell tile defined by the ...
Abstract: Multimodal Emotion and Intent Joint Understanding (MEIJU) aims to decode the semantic information expressed in the multimodal dialogues while inferring the emotions and intents, providing ...
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