Evidence map›Paper›PMID 40156641›Full record

ArticleJournal of mathematical biology2025

Single-cell 3D genome reconstruction in the haploid setting using rigidity theory.

Sean Dewar, Georg Grasegger, Kaie Kubjas, Fatemeh Mohammadi, Anthony Nixon

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Article in Journal of mathematical biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Sean DewarSchool of Mathematics, University of Bristol, Bristol, UK.
Georg GraseggerJohann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, Linz, Austria.ORCID 0000-0001-7421-8115
Kaie KubjasDepartment of Mathematics and Systems Analysis, Aalto University, Espoo, Finland. kaie.kubjas@aalto.fi.ORCID 0000-0002-2227-2272
Fatemeh MohammadiDepartments of Mathematics and Computer Science, KU Leuven, Leuven, Belgium.ORCID 0000-0001-5187-0995
Anthony NixonMathematics and Statistics, Lancaster University, Lancaster, UK.

Funding

Austrian Science Fund 10.55776/P31888Engineering and Physical Sciences Research Council EP/X036723/1FWO G023721NFWO G0F5921NKU Leuven iBOF/23/064UiT Aurora MASCOT projectWellcome Trust 323416
6 · The paper itself

Abstract

This article considers the problem of 3-dimensional genome reconstruction for single-cell data, and the uniqueness of such reconstructions in the setting of haploid organisms. We consider multiple graph models as representations of this problem, and use techniques from graph rigidity theory to determine identifiability. Biologically, our models come from Hi-C data, microscopy data, and combinations thereof. Mathematically, we use unit ball and sphere packing models, as well as models consisting of distance and inequality constraints. In each setting, we describe and/or derive new results on realisability and uniqueness. We then propose a 3D reconstruction method based on semidefinite programming and apply it to synthetic and real data sets using our models.

Indexed as

GenomeHaploidyImaging, Three-DimensionalModels, GeneticSingle-Cell AnalysisAnimalsComputer SimulationHumansMathematical Concepts3D genome reconstructionHi-CRigiditySemidefinite programming

Identifiers

PMID40156641
PMCPMC11954715

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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.