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EPCOT Data

EPCOT v2 is a general AI model that predicts cell type-specific/context-specific regulatory signals from ATAC-seq data and DNA sequences.

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Predicted Modalities

• Nascent transcription signals (e.g., PRO-seq, GRO-seq, TT-seq, Bru-seq)
• Gene expression profiles from total and polyA+ RNA-seq
• Transcription factor binding and histone modifications
• 3D chromatin organization, including Micro-C, Hi-C, and ChIA-PET contact maps
• Transcription initiation signals (e.g., CAGE-seq, GRO-cap, PRO-cap)
• Synthetic enhancer activity measured by STARR-seq

GitHub — liu-bioinfo-lab/general_AI_model

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