gene expression
PulseAugur coverage of gene expression — every cluster mentioning gene expression across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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New REST framework predicts gene expression from tissue images
Researchers have developed a new framework called REST (Reliability-Guided Spatial Transcriptomics supervision) to predict gene expression from histopathological HE-stained images. This method uses a Biological Program …
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VGL-stGen: Multimodal model links lung histology and gene expression
Researchers have developed VGL-stGen, a multimodal large language model that integrates lung histology images with spatial transcriptomics data. This model, adapted from a pretrained medical vision-language model, uses …
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New REST framework predicts molecular data from H&E images
Researchers have developed a new framework called REST (Reliability-Guided Spatial Transcriptomics) to predict molecular information from H&E-stained histopathological images. This method utilizes a Biological Program B…
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New Diffusion Model Predicts Gene Expression from Histology Images
Researchers have developed a novel method for predicting gene expression from histology images by reformulating the task as a conditional generation problem within the transcriptional program space. This approach utiliz…
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New COAST framework enhances gene expression prediction in spatial transcriptomics
Researchers have developed COAST, a novel framework for predicting gene expression in spatial transcriptomics using histology images. This context-aware differential learning approach leverages both local and global con…
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New AI Framework Integrates Multi-Omics Data for Cancer Research
Researchers have developed a new framework called Pathway Activity Autoencoders to integrate multi-omics data for cancer research. This approach embeds prior biological knowledge into the model's architecture, enhancing…
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New GC-MoE model predicts cell gene expression from histology images
Researchers have developed GC-MoE, a novel method for estimating gene expression in individual cells from histopathological images. This approach utilizes a Mixture-of-Experts model guided by genomics to predict cell-ty…
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PerturbedVAE framework improves single-cell prediction by separating gene expression signals
Researchers have developed PerturbedVAE, a new framework to improve single-cell perturbation prediction by addressing the imbalance between perturbation-invariant and perturbation-specific gene expression signals. Exist…