Deep learning models for studying IPF and fibrotic diseases (IMAGE)
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(A) This paper presents two deep learning models: an omicstransformer that generates differential gene expression profiles from text prompts and a pathway-aware aging clock trained on UK Biobank proteomics data. The models focus on IPF-relevant biological pathways including TGF-β signaling, oxidative stress, inflammation, and ECM remodeling.
(B) Architecture of the pathway-aware proteomic aging clock. The neural network processes protein measurements through feature extraction layers that branch into age prediction and pathway-specific attention mechanisms, enabling interpretable aging predictions with pathway awareness.
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Insilico Medicine
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