Genome-wide association studies (GWAS) have associated 76 loci with the risk of developing melanoma. However, understanding the molecular basis of such associations has remained a challenge because most of these loci are in non-coding regions of the genome. Here, we integrated data on epigenomic markers, three-dimensional (3D) genome organization, and expression quantitative trait loci (eQTL) from melanoma-relevant tissues and cell types to gain novel insights into the mechanisms underlying melanoma risk.
View Article and Find Full Text PDFIntroduction: Asthma is a heterogeneous inflammatory disease often associated with other complex phenotypes. Identifying asthma-associated diseases and uncovering the molecular mechanisms mediating their interaction can help detangle the heterogeneity of asthma. Network analysis is a powerful approach for untangling such inter-disease relationships.
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