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- W3015754908 abstract "Hi-C data is important for studying chromatin three-dimensional (3D) structure. However, the resolution of most existing Hi-C data is generally coarse due to sequencing cost. Therefore, it will be helpful if we can predict high-resolution Hi-C data from low-coverage sequencing data. Here we developed a novel and simple computational method based on deep learning named SRHiC to enhance the resolution of Hi-C data. We verified SRHiC on Hi-C data in human cell line. We also evaluated the generalization power of SRHiC by enhancing Hi-C data resolution in other human and mouse cell types. Results showed that SRHiC outperforms the state-of-the-art methods in accuracy of prediction." @default.
- W3015754908 created "2020-04-17" @default.
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- W3015754908 date "2020-04-08" @default.
- W3015754908 modified "2023-10-09" @default.
- W3015754908 title "SRHiC: A Deep Learning Model to Enhance the Resolution of Hi-C Data" @default.
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- W3015754908 doi "https://doi.org/10.3389/fgene.2020.00353" @default.
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