Evidence map›Paper›PMID 31015419›Full record

ReviewNature communications2019

Humanising the mouse genome piece by piece.

Fei Zhu, Remya R Nair, Elizabeth M C Fisher, Thomas J Cunningham

Abstract readReview
In one paragraph

Review in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.

0numbers the graph read from it
0cells of the map it votes in
72citing 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

72 citing papers in PubMed.

  1. LncRNAEpigenetics · 2026
    Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Review
  8. Article
  9. Review
  10. Computational modeling of human genetic variants in mice.bioRxiv : the preprint server for biology · 2025
    Article
  11. Drug repurposing in amyotrophic lateral sclerosis (ALS).Expert opinion on drug discovery · 2025
    Review
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review

12 more citing papers are in PubMed but not listed here.

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

4 authors.

Fei ZhuDepartment of Neuromuscular Diseases, Institute of Neurology, University College London, London, WC1N 3BG, UK.
Remya R NairMammalian Genetics Unit, MRC Harwell Institute, Oxfordshire, OX11 0RD, UK.
Elizabeth M C FisherDepartment of Neuromuscular Diseases, Institute of Neurology, University College London, London, WC1N 3BG, UK. elizabeth.fisher@ucl.ac.uk.ORCID http://orcid.org/0000-0003-2850-9936
Thomas J CunninghamMammalian Genetics Unit, MRC Harwell Institute, Oxfordshire, OX11 0RD, UK.ORCID http://orcid.org/0000-0002-4751-3140

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To better understand human health and disease, researchers create a wide variety of mouse models that carry human DNA. With recent advances in genome engineering, the targeted replacement of mouse genomic regions with orthologous human sequences has become increasingly viable, ranging from finely tuned humanisation of individual nucleotides and amino acids to the incorporation of many megabases of human DNA. Here, we examine emerging technologies for targeted genomic humanisation, we review the spectrum of existing genomically humanised mouse models and the insights such models have provided, and consider the lessons learned for designing such models in the future.

Indexed as

Models, AnimalAnimalsChromosomes, HumanGene EditingGene Transfer TechniquesGenome, HumanHumansMiceMice, TransgenicResearch Design

Identifiers

PMID31015419
PMCPMC6478830

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.