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Analiza ATAC-seq×Analiza Hi-C×
DziedzinaGenetykaGenetyka
RodzinaProcess / pipelineProcess / pipeline
Rok powstania20132009
TwórcaJason Buenrostro, Paul Giresi & William GreenleafErez Lieberman-Aiden & Job Dekker
TypChromatin profiling methodChromatin interaction method
Źródło pierwotneBuenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013). Transposition of native chromatin for fast and sensitive epigenomic profiling of cell populations and tissues. Nature Methods, 10(12), 1213–1218. link ↗Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., & Dekker, J. (2009). Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science, 326(5950), 289–293. DOI ↗
Inne nazwyChromatin accessibility, Open chromatin, Accessible chromatin analysisChromosome conformation capture, 3D genome, Chromatin contact mapping
Pokrewne22
PodsumowanieATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) is a method for profiling the landscape of chromatin accessibility genome-wide. Developed by Buenrostro and colleagues in 2013, ATAC-seq uses hyperactive transposase to tag open, accessible chromatin regions, enabling rapid and sensitive identification of regulatory DNA elements. ATAC-seq has become a standard technique for characterizing gene regulatory landscapes, discovering cell-type-specific regulatory elements, and inferring gene regulatory networks.Hi-C (High-Chromosome Conformation Capture) is a technique and associated computational methods for mapping the 3D architecture of the genome within cells. Developed by Lieberman-Aiden and Dekker in 2009, Hi-C identifies physical interactions between genomic regions that may be distant in linear sequence but spatially proximal in 3D nuclear space. Hi-C analysis has revealed fundamental principles of genome organization, including the existence of topologically associating domains (TADs), and provides insights into how 3D structure regulates gene expression and DNA replication.
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ScholarGatePorównaj metody: ATAC-seq Analysis · Hi-C Analysis. Pobrano 2026-06-17 z https://scholargate.app/pl/compare