Evidence map›Paper›PMID 27786255›Full record

ArticleScientific reports2016

Hi-C-constrained physical models of human chromosomes recover functionally-related properties of genome organization.

Marco Di Stefano, Jonas Paulsen, Tonje G Lien, Eivind Hovig, Cristian Micheletti

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
–field-weighted citation impact
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

37 citing papers in PubMed.

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  12. Satellite DNAs and human sex chromosome variation.Seminars in cell & developmental biology · 2022
    Review
  13. Article
  14. Article
  15. Uncovering the Principles of Genome Folding by 3D Chromatin Modeling.Cold Spring Harbor perspectives in biology · 2022
    Review
  16. Review
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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

5 authors.

Marco Di StefanoSISSA, International School for Advanced Studies, Trieste, I-34136, Italy.
Jonas PaulsenInstitute of Basic Medical Sciences, University of Oslo, Oslo, 0317, Norway.
Tonje G LienUniversity of Oslo, Department of Mathematics, Oslo, 0316, Norway.
Eivind HovigInstitute for Cancer Research, Oslo University Hospital, Department of Tumor Biology, Oslo, 0310, Norway.
Cristian MichelettiSISSA, International School for Advanced Studies, Trieste, I-34136, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Combining genome-wide structural models with phenomenological data is at the forefront of efforts to understand the organizational principles regulating the human genome. Here, we use chromosome-chromosome contact data as knowledge-based constraints for large-scale three-dimensional models of the human diploid genome. The resulting models remain minimally entangled and acquire several functional features that are observed in vivo and that were never used as input for the model. We find, for instance, that gene-rich, active regions are drawn towards the nuclear center, while gene poor and lamina associated domains are pushed to the periphery. These and other properties persist upon adding local contact constraints, suggesting their compatibility with non-local constraints for the genome organization. The results show that suitable combinations of data analysis and physical modelling can expose the unexpectedly rich functionally-related properties implicit in chromosome-chromosome contact data. Specific directions are suggested for further developments based on combining experimental data analysis and genomic structural modelling.

Indexed as

Genome, HumanModels, GeneticCell LineChromosome SegregationChromosomes, HumanDatabases, GeneticDiploidyFibroblastsHuman Embryonic Stem CellsHumansImaging, Three-Dimensional

Identifiers

PMID27786255
PMCPMC5081523

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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.