Improving comparative analyses of Hi-C data via contrastive self-supervised learning

Abstract Hi-C is a widely applied chromosome conformation capture (3C)-based technique, which has produced a large number of genomic contact maps with high sequencing depths for a wide range of cell types, enabling comprehensive analyses of the relationships between biological functionalities (e.g....

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Veröffentlicht in:	Briefings in bioinformatics 2023-07, Vol.24 (4)
Hauptverfasser:	Li, Han, He, Xuan, Kurowski, Lawrence, Zhang, Ruotian, Zhao, Dan, Zeng, Jianyang
Format:	Artikel
Sprache:	eng
Schlagworte:	Chromatin Chromosomes Comparative analysis Conformation Data analysis Gene expression Gene mapping Gene regulation Genomics Reproducibility Self-supervised learning Sequences Three dimensional analysis
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