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Bayesian Inference of Spatial Organizations of Chromosomes
2013
PLoS Computational Biology
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Knowledge of spatial chromosomal organizations is critical for the study of transcriptional regulation and other nuclear processes in the cell. ...
Here we describe a novel Bayesian probabilistic approach, denoted as "Bayesian 3D constructor for Hi-C data" (BACH), to infer the consensus 3D chromosomal structure. ...
(G) Spatial organization of H3K36me3. OR = 10.91, p-value = 1.0e-7. (H) Spatial organization of H3K27me3. OR = 2.17, p-value = 0.0706. (I) Spatial organization of H3K4me3. ...
doi:10.1371/journal.pcbi.1002893
pmid:23382666
pmcid:PMC3561073
fatcat:znpjgb7vnngnnhgcxk2qbn6hde
Inferential modeling of 3D chromatin structure
2015
Nucleic Acids Research
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to decode the 3D organization of the genome. ...
Understanding 3D spatial arrangements of chromosomes and revealing longrange chromatin interactions are critical to decipher these biological processes. ...
We thank Mr Huichao Gong, Mr Chao He and Mr Yuexin Wu for their helpful discussions at the early stage of this research. ...
doi:10.1093/nar/gkv100
pmid:25690896
pmcid:PMC4417147
fatcat:adrcqsbbnza7blmslvvennwbuy
Bayesian Reconstruction of Chromatin Conformation from FISH and Hi-C Data
2013
Biophysical Journal
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Single-cell imaging and chromosome conformation capture-based techniques provide information on chromosome conformations and their spatial organizations. ...
Here, we present such objective, Bayesian procedure that infers the least-biased distribution of chromatin conformational states from FISH and Hi-C datasets accounting both for heterogeneity in the underlying ...
doi:10.1016/j.bpj.2012.11.3228
fatcat:xqyixntkbjg3hjn3cllyrvqixm
Hierarchical Markov Random Field model captures spatial dependency in gene expression, demonstrating regulation via the 3D genome
[article]
2019
bioRxiv
pre-print
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The inference of PhiMRF follows a Bayesian framework, and we introduce the Spatial Interaction Estimate (SIE) to measure the strength of spatial dependency in gene expression. ...
We also report high inter-chromosomal spatial correlations in the majority of chromosome pairs, as well as the whole genome. ...
Bayesian Inference
244 The goal of our Bayesian framework is to simulate from the posterior distributions p(α|y), p(η|y) and p(τ 2 |y). ...
doi:10.1101/2019.12.16.878371
fatcat:og5mvg3mfna6fhhwjiwyo2lq6q
Computational inference of physical spatial organization of eukaryotic genomes
2016
Quantitative Biology
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Here, we review the current computational models that simulate chromosome dynamics, and explain the physical and topological properties of chromosomal conformation, as inferred from these newly generated ...
Results: Thanks to recent technological developments, we can now probe chromatin interaction in substantial detail, boosting research interest in modeling genome spatial organization. ...
This work was supported by grants from the National Nature Science
COMPLIANCE WITH ETHICS GUIDELINES The authors Bingxiang Xu and Zhihua Zhang declare that they have no conflict of interests. ...
doi:10.1007/s40484-016-0082-1
fatcat:qqmw3srpsfa4rn4gqfzosy66qy
Seevolution: visualizing chromosome evolution
2009
Bioinformatics
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As methods to infer evolutionary histories of genomes become increasingly complex, visualization of the evolutionary process will not only be useful for communication, but will also serve as an exploratory ...
Multiple organisms related by a phylogeny can be visualized simultaneously. ...
Each segment can be assigned a color and a texture, and Seevolution uses these colors to communicate information about breakpoints of rearrangement, spatial organization of the chromosome such as distance ...
doi:10.1093/bioinformatics/btp096
pmid:19233896
pmcid:PMC2660879
fatcat:bf6xmxxzxndmllnwnqgsd4y72a
Bayesian inference of chromatin structure ensembles from population-averaged contact data
2020
Proceedings of the National Academy of Sciences of the United States of America
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Here, we propose a fully Bayesian method to infer ensembles of chromatin structures and to determine the optimal number of states in a principled, objective way. ...
Mounting experimental evidence suggests a role for the spatial organization of chromatin in crucial processes of the cell nucleus such as transcription regulation. ...
our approach to deliver insights into chromatin organization of great biological relevance. chromosome conformation capture | genome structure modeling | Bayesian inference | model comparison I n recent ...
doi:10.1073/pnas.1910364117
pmid:32193349
fatcat:acuu3ksa3ra7nd5y6fldc5325e
Optical Tweezers Controlled Nanopore Detection of Nucleosomes along a DNA
2013
Biophysical Journal
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Single-cell imaging and chromosome conformation capture-based techniques provide information on chromosome conformations and their spatial organizations. ...
Here, we present such objective, Bayesian procedure that infers the least-biased distribution of chromatin conformational states from FISH and Hi-C datasets accounting both for heterogeneity in the underlying ...
doi:10.1016/j.bpj.2012.11.3225
fatcat:of6lliqglnedhhrfz4l73wv4o4
The Architects of the Archaeal Chromatin
2013
Biophysical Journal
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Single-cell imaging and chromosome conformation capture-based techniques provide information on chromosome conformations and their spatial organizations. ...
Here, we present such objective, Bayesian procedure that infers the least-biased distribution of chromatin conformational states from FISH and Hi-C datasets accounting both for heterogeneity in the underlying ...
doi:10.1016/j.bpj.2012.11.3226
fatcat:jlo4hhxrmnednean75kjaqfuii
Population Properties of Self-Avoiding Polymer Chain Models of Chromosomes in a Confined Space of Nucleus
2013
Biophysical Journal
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Single-cell imaging and chromosome conformation capture-based techniques provide information on chromosome conformations and their spatial organizations. ...
Here, we present such objective, Bayesian procedure that infers the least-biased distribution of chromatin conformational states from FISH and Hi-C datasets accounting both for heterogeneity in the underlying ...
doi:10.1016/j.bpj.2012.11.3229
fatcat:dd3stakm7zeatcwo4q4ys7fj5a
Modeling Long Chromatin Fibers based on In-Vivo Nucleosome Positioning Maps
2013
Biophysical Journal
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Single-cell imaging and chromosome conformation capture-based techniques provide information on chromosome conformations and their spatial organizations. ...
Here, we present such objective, Bayesian procedure that infers the least-biased distribution of chromatin conformational states from FISH and Hi-C datasets accounting both for heterogeneity in the underlying ...
doi:10.1016/j.bpj.2012.11.3227
fatcat:sfycdykbfnhkhb27stuctenq54
FastHiC: a fast and accurate algorithm to detect long-range chromosomal interactions from Hi-C data
2016
Bioinformatics
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by modeling the correlated peak status of neighboring loci pairs and the inference of hidden dependency structure. ...
In our previous work, we have developed a novel hidden Markov random field (HMRF) based Bayesian method, which through explicitly modeling the non-negligible spatial dependency among adjacent pairs of ...
Introduction The spatial organizations of chromosomes play a critical role in transcription regulation. ...
doi:10.1093/bioinformatics/btw240
pmid:27153668
pmcid:PMC5013904
fatcat:px6xcpuy5vb6be3vuako2nvltq
Predicting the spatial organization of chromosomes using epigenetic data
2015
Genome Biology
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Chromosome folding can reinforce the demarcation between euchromatin and heterochromatin. ...
Such computational approaches reinforce the idea of a linkage between epigenetically marked chromatin domains and their segregation into distinct compartments at the megabase scale or topological domains ...
Introduction The ability to probe the spatial organization of chromosomes through the combination of chromosome conformation capture methods with high-throughput sequencing (3C-Hi-C) has revealed how chromosomes ...
doi:10.1186/s13059-015-0752-8
pmid:26319942
pmcid:PMC4552987
fatcat:qdh4rowbcvbjjh56xxremyluji
Detection of gene copy number changes in CGH microarrays using a spatially correlated mixture model
2006
Computer applications in the biosciences : CABIOS
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Inference is performed in a Bayesian framework. From the output, posterior probabilities of belonging to each of the three states are estimated for each genomic sequence and used to classify them. ...
between sequences along the chromosome. ...
Conflict of Interest: none declared. ...
doi:10.1093/bioinformatics/btl035
pmid:16455750
fatcat:jn5ugv7tqfbvne7an3wjvnwna4
GEM: A manifold learning based framework for reconstructing spatial organizations of chromosomes
[article]
2017
bioRxiv
pre-print
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Decoding the spatial organizations of chromosomes has crucial implications for studying eukaryotic gene regulation. ...
organizations of chromosomes from Hi-C data. ...
In [19] , an expectation-maximization based algorithm was proposed to infer the 3D chromatin organizations under a Bayesian inference framework. ...
doi:10.1101/161208
fatcat:nkx7kzvqazhdrdwjlv57lhpk3q
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