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Leveraging Hi-C Data to Detect Chromosomal Reorganizations
The three-dimensional (3D) organization of genomes refers to the spatial organization and folding of chromatin within the nucleus of cells. Over the years, the initial development and subsequent applications of chromosome capture techniques (3C) and their derivatives have permitted the study of the 3D genome organization at the deepest level of ...Lucía, Álvarez-González +1 more
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Deciphering 3D Organization of Chromosomes Using Hi-C Data
2018In order to interpret data from Hi-C studies genome-wide contact probability maps need to be translated into models of functional 3D genome organization. Here, we first present an overview of computational methods to analyze contact probability maps in terms of features such as the level and shape of compartmentalization.
Hofmann, A, Heermann, DW
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A technique for preserving network structure in randomized Hi-C data
Journal of Bioinformatics and Computational BiologyChromatin interaction data are frequently analyzed as a network to study several aspects of chromatin structure. Hi-C experiments are costly and there is a need to create simulated networks for quality assessment or result validation purposes. Existing tools do not maintain network properties during randomization.
Andrejs Sizovs +6 more
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HiCTF:A Transformer Model for enhancing Hi-C data resolution
Proceedings of the 2023 10th International Conference on Biomedical and Bioinformatics Engineering, 2023Xuemin Zhao +2 more
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