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Our comprehensive database integrates data from scRNA seq and sc-ATAC seq, identifying cis-regulatory elements (CREs) through comparison with ENCODE, Epimap, GWAS Catalog, and other datasets. By connecting transcription factors (TFs), CREs, and target genes, cEpiReg unveils hidden regulatory links crucial for understanding AD pathogenesis.

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cEpiReg

cEpiReg constructs a comprehensive database elucidating the intricate regulatory mechanisms underlying Alzheimer's Disease (AD) genetics. Through integrating data from scRNA seq and sc-ATAC seq, we identified the cis-regulatory elements (CREs) by comparing our results against various databases like ENCODE, Epimap, GWAS Catalog, and publicly available datasets. This project establishes a robust framework connecting transcription factors (TFs), CREs, and target genes. cEpiReg uncovers hidden regulatory links that could piece together missing links crucial for understanding AD pathogenesis.

Website can be reached at https://bioed.bu.edu/students_24/Team_10/Team-10_database.html

Created by Neha Rao, Bhavana Kapalli, and Jawahar Mahendran

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Our comprehensive database integrates data from scRNA seq and sc-ATAC seq, identifying cis-regulatory elements (CREs) through comparison with ENCODE, Epimap, GWAS Catalog, and other datasets. By connecting transcription factors (TFs), CREs, and target genes, cEpiReg unveils hidden regulatory links crucial for understanding AD pathogenesis.

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