Evidence map›Paper›PMID 38654598›Full record

ArticleBriefings in functional genomics2024

Genome structural dynamics: insights from Gaussian network analysis of Hi-C data.

Anupam Banerjee, She Zhang, Ivet Bahar

Open access · hybridAbstract read
In one paragraph

Article in Briefings in functional genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 94% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Anupam BanerjeeLaufer Center for Physical & Quantitative Biology, Stony Brook University, NY 11794, USA.ORCID 0000-0002-2859-7705
She ZhangOpenEye, Cadence Molecular Sciences, Santa Fe, NM 87508, USA.
Ivet BaharLaufer Center for Physical & Quantitative Biology, Stony Brook University, NY 11794, USA.ORCID 0000-0001-9959-4176
Stony Brook School · USStony Brook University · US

Funding

Toward a Deeper Understanding of Allostery and Allotargeting by Computational ApproachesR01GM139297 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Ivet Bahar · 2021 to 2026
$2.8M
NIGMS NIH HHS R01 GM139297NIH HHS R01 GM139297
6 · The paper itself

Abstract

Characterization of the spatiotemporal properties of the chromatin is essential to gaining insights into the physical bases of gene co-expression, transcriptional regulation and epigenetic modifications. The Gaussian network model (GNM) has proven in recent work to serve as a useful tool for modeling chromatin structural dynamics, using as input high-throughput chromosome conformation capture data. We focus here on the exploration of the collective dynamics of chromosomal structures at hierarchical levels of resolution, from single gene loci to topologically associating domains or entire chromosomes. The GNM permits us to identify long-range interactions between gene loci, shedding light on the role of cross-correlations between distal regions of the chromosomes in regulating gene expression. Notably, GNM analysis performed across diverse cell lines highlights the conservation of the global/cooperative movements of the chromatin across different types of cells. Variations driven by localized couplings between genomic loci, on the other hand, underlie cell differentiation, underscoring the significance of the four-dimensional properties of the genome in defining cellular identity. Finally, we demonstrate the close relation between the cell type-dependent mobility profiles of gene loci and their gene expression patterns, providing a clear demonstration of the role of chromosomal 4D features in defining cell-specific differential expression of genes.

Indexed as

ChromatinGenomeHumansNormal DistributionChromatin4D Genomicschromatin dynamicsGaussian network model (GNM)gene expression regulationgenome hierarchical organizationHi-C

Identifiers

PMID38654598
PMCPMC11428154
OpenAlexW4395095699

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.