Results 41 to 50 of about 39,833,464 (257)
NeoHiC: A Web Application for the Analysis of Hi-C Data [PDF]
, 2020 High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of chromatin interactions and 3D chromosome folding on a larger scale. A graph-based multi-level representation of Hi-C data is essential for proper visualisation of the spatial pattern they represent, in particular for comparing different experiments or for re-mapping ...
D'Agostino D +3 more
openaire +8 more sources
Computational Processing and Quality Control of Hi-C, Capture Hi-C and Capture-C Data [PDF]
Genes, 2019 Hi-C, capture Hi-C (CHC) and Capture-C have contributed greatly to our present understanding of the three-dimensional organization of genomes in the context of transcriptional regulation by characterizing the roles of topological associated domains, enhancer promoter loops and other three-dimensional genomic interactions.
Peter Hansen +6 more
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Hi-C interaction map on GM12878 HiC data.
, 2022 Heatmap showing the raw read count of interactions at 5k bins of chr21 (36000kb to 39500kb) (same region as S10 Fig in the cLoops paper [43] on the GM12878 Hi-C dataset in Rao et al. [5]. The heatmap is colored based on the log of read count. Significant
Hamid Alinejad-Rokny (518381) +6 more
core +1 more source
Reference panel guided topological structure annotation of Hi-C data
Nature Communications, 2022 Predicting topological structures from Hi-C data provides insight into comprehending gene expression and regulation. Here, the authors present RefHiC, an attention-based deep learning framework that leverages a reference panel of Hi-C datasets to assist ...
Yanlin Zhang, Mathieu Blanchette
doaj +1 more source
qc3C: Reference-free quality control for Hi-C sequencing data.
PLoS Computational Biology, 2021 Hi-C is a sample preparation method that enables high-throughput sequencing to capture genome-wide spatial interactions between DNA molecules. The technique has been successfully applied to solve challenging problems such as 3D structural analysis of ...
Matthew Z DeMaere, Aaron E Darling
doaj +1 more source
Hi-C maps, 3D communities, and domains.
, 2023 (a) Hi-C maps where the red-to-blue pixel colors are a proxy for short-to-long 3D distances. The squares decorating the map’s diagonals represent GenLouvain-derived 3D communities for three γ values (0.5, 0.6, and 0.7).
Dolores Bernenko (16528426) +3 more
core +1 more source
SRHiC: A Deep Learning Model to Enhance the Resolution of Hi-C Data
Frontiers in Genetics, 2020 Hi-C data is important for studying chromatin three-dimensional structure. However, the resolution of most existing Hi-C data is generally coarse due to sequencing cost.
Zhilan Li, Zhiming Dai, Zhiming Dai
doaj +1 more source
scHiCTools: A computational toolbox for analyzing single-cell Hi-C data.
PLoS Computational Biology, 2021 Single-cell Hi-C (scHi-C) sequencing technologies allow us to investigate three-dimensional chromatin organization at the single-cell level. However, we still need computational tools to deal with the sparsity of the contact maps from single cells and ...
Xinjun Li +4 more
doaj +1 more source
Memory-Optimised Parallel Processing of Hi-C Data [PDF]
2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, 2015 This paper presents the optimisation efforts on the creation of a graph-based mapping representation of gene adjacency. The method is based on the Hi-C process, starting from Next Generation Sequencing data, and it analyses a huge amount of static data in order to produce maps for one or more genes.
DROCCO, MAURIZIO +4 more
openaire +1 more source
BMC Bioinformatics, 2022 Background Understanding the role of various factors in 3D genome organization is essential to determine their impact on shaping large-scale chromatin units such as euchromatin (A) and heterochromatin (B) compartments. At this level, chromatin compaction
Mikhail D. Magnitov +4 more
doaj +1 more source