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Chromosome interaction data
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Current computational methods on Hi-C analysis focused on identifying Mb-size domains often failed to unveil the underlying functional and mechanistic relationship of chromatin structure and gene regulation. We developed a novel computational method HiSIF to identify genome-wide interacting loci.
13p
vibransone
28-03-2024
7
2
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We present HiGlass, an open source visualization tool built on web technologies that provides a rich interface for rapid, multiplex, and multiscale navigation of 2D genomic maps alongside 1D genomic tracks, allowing users to combine various data types, synchronize multiple visualization modalities, and share fully customizable views with others.
12p
vigalileogalilei
27-02-2022
13
1
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The three-dimensional (3D) organization of chromosomes can be probed using methods like Capture-C. However, it is unclear how such population-level data relate to the organization within a single cell, and the mechanisms leading to the observed interactions are still largely obscure. We present a polymer modeling scheme based on the assumption that chromosome architecture is maintained by protein bridges, which form chromatin loops.
16p
viaristotle
29-01-2022
17
1
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Chromosome conformation capture methods are being increasingly used to study three-dimensional genome architecture in multiple cell types and species. An important challenge is to examine changes in three-dimensional architecture across cell types and species. We present Arboretum-Hi-C, a multi-task spectral clustering method, to identify common and context-specific aspects of genome architecture.
18p
viaristotle
29-01-2022
7
0
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Capture Hi-C (CHi-C) is a method for profiling chromosomal interactions involving targeted regions of interest, such as gene promoters, globally and at high resolution. Signal detection in CHi-C data involves a number of statistical challenges that are not observed when using other Hi-C-like techniques.
17p
viaristotle
29-01-2022
4
0
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Hi-C is a popular technique to map three-dimensional chromosome conformation. In principle, Hi-C’s resolution is only limited by the size of restriction fragments. However, insufficient sequencing depth forces researchers to artificially reduce the resolution of Hi-C matrices at a loss of biological interpretability.
15p
viarchimedes
26-01-2022
9
0
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The three-dimensional conformation of a genome can be profiled using Hi-C, a technique that combines chromatin conformation capture with high-throughput sequencing. However, structural variations often yield features that can be mistaken for chromosomal interactions.
15p
viarchimedes
26-01-2022
11
0
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An important unanswered question in chromatin biology is the extent to which long-range looping interactions change across developmental models, genetic perturbations, drug treatments, and disease states. Computational tools for rigorous assessment of cell type-specific loops across multiple biological conditions are needed.
44p
viarchimedes
26-01-2022
10
1
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The development of chromosomal conformation capture techniques, particularly, the Hi-C technique, has made the analysis and study of the spatial conformation of a genome an important topic in bioinformatics and computational biology. Aided by high-throughput next generation sequencing techniques, the Hi-C technique can generate genome-wide, large-scale intra- and inter-chromosomal interaction data capable of describing in details the spatial interactions within a genome.
17p
vibeauty
23-10-2021
9
0
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Knowledge of the three-dimensional structure of the genome is necessary to understand how gene expression is regulated. Recent experimental techniques such as Hi-C or ChIA-PET measure long-range chromatin interactions genome-wide but are experimentally elaborate, have limited resolution and such data is only available for a limited number of cell types and tissues.
15p
visilicon2711
20-08-2021
9
1
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More and more 3C/Hi-C experiments on prokaryotes have been published. However, most of the published modeling tools for chromosome 3D structures are targeting at eukaryotes. How to transform prokaryotic experimental chromosome interaction data into spatial structure models is an important task and in great need.
10p
visilicon2711
20-08-2021
5
1
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Hi-C is a molecular biology technique to understand the genome spatial structure. However, data obtained from Hi-C experiments is biased. Therefore, several methods have been developed to model Hi-C data and identify significant interactions.
10p
vijeeni2711
24-07-2021
8
0
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Dynamic visualisation interfaces are required to explore the multiple microbial genome data now available, especially those obtained by high-throughput sequencing — a.k.a. “Next-Generation Sequencing” (NGS) — technologies; they would also be useful for “standard” annotated genomes whose chromosome organizations may be compared.
9p
viwyoming2711
16-12-2020
8
1
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A variety of DNA binding proteins are involved in regulating and shaping the packing of chromatin. They aid the formation of loops in the DNA that function to isolate different structural domains.
12p
vikentucky2711
24-11-2020
11
1
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Molecular interactions between proteins and DNA molecules underlie many cellular processes, including transcriptional regulation, chromosome replication, and nucleosome positioning. Computational analyses of protein-DNA interactions rely on experimental data characterizing known protein-DNA interactions structurally and biochemically.
19p
vioklahoma2711
19-11-2020
9
1
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Assays that are capable of detecting genome-wide chromatin interactions have produced massive amount of data and led to great understanding of the chromosomal three-dimensional (3D) structure. As technology becomes more sophisticated, higher-and-higher resolution data are being produced, going from the initial 1 Megabases (Mb) resolution to the current 10 Kilobases (Kb) or even 1 Kb resolution.
13p
vioklahoma2711
19-11-2020
6
1
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Normalization is essential to ensure accurate analysis and proper interpretation of sequencing data, and chromosome conformation capture data such as Hi-C have particular challenges. Although several methods have been proposed, the most widely used type of normalization of Hi-C data usually casts estimation of unwanted effects as a matrix balancing problem, relying on the assumption that all genomic regions interact equally with each other.
16p
viconnecticut2711
28-10-2020
10
1
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Changes in spatial chromatin interactions are now emerging as a unifying mechanism orchestrating the regulation of gene expression. Hi-C sequencing technology allows insight into chromatin interactions on a genome-wide scale. However, Hi-C data contains many DNA sequence- and technology-driven biases.
10p
viconnecticut2711
28-10-2020
14
1
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Genome-wide association studies (GWAS) are typically visualized using a two-dimensional Manhattan plot, displaying chromosomal location of SNPs along the x-axis and the negative log-10 of their p-value on the yaxis.
8p
vicolorado2711
22-10-2020
6
0
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