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Hilbert curves can be used to effectively visualize genomic data, because they can provide a global overview of genome-scale datasets while still revealing the spatial distribution of features at high resolution (Anders, 2009). Hilbert curve visualization has been utilized to compare the sequence difference between human and other primates (Wong, 2014), to show the spatial organization of different chromatin states (Kharchenko et al., 2011), and to investigate the genome-wide distribution of histone modifications (Anders 2009, Henry et al., 2012).
(Anders, 2009) Visualization of genomic data with the Hilbert curve. Bioinformatics.
(Wong, 2014) Tiny genetic difference between humans and other primates pervade the genome. Sci. Am.
(Kharchenko et al., 2011) Comprehensive analysis of the chromatin landscape in Drosophila melanogaster. Nature.
(Henry et al., 2012) Cell type-specific genomics of Drosophila neurons. Nucleic Acids Res.
(Gu et al., 2016) HilbertCurve: an R/Bioconductor package for high-resolution visualization of genomic data. Bioinformatics.