Evidence map›Paper›PMID 29666443›Full record

ReviewNature reviews. Molecular cell biology2018

Single-cell transcriptional profiling: a window into embryonic cell-type specification.

Blanca Pijuan-Sala, Carolina Guibentif, Berthold Göttgens

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Molecular cell biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Cell Trafficking at the Intersection of the Tumor-Immune Compartments.Annual review of biomedical engineering · 2022
    Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. In vivo and ex vivo haematopoietic stem cell expansion.Current opinion in hematology · 2020
    Review
  19. Article
  20. Article
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.

Blanca Pijuan-SalaWellcome and MRC Cambridge Stem Cell Institute and the Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.
Carolina GuibentifWellcome and MRC Cambridge Stem Cell Institute and the Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK.
Berthold GöttgensWellcome and MRC Cambridge Stem Cell Institute and the Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK. bg200@cam.ac.uk.ORCID 0000-0001-6302-5705

Funding

Medical Research Council MC_PC_12009Medical Research Council MR/M008975/1
6 · The paper itself

Abstract

During mammalian embryonic development, a single fertilized egg cell will proliferate and differentiate into all the cell lineages and cell types that eventually form the adult organism. Cell lineage diversification involves repeated cell fate choices that ultimately occur at the level of the individual cell rather than at the cell-population level. Improvements in single-cell technologies are transforming our understanding of mammalian development, not only by overcoming the limitations presented by the extremely low cell numbers of early embryos but also by enabling the study of cell fate specification in greater detail. In this Review, we first discuss recent advances in single-cell transcriptomics and imaging and provide a brief outline of current bioinformatics methods available to analyse the resulting data. We then discuss how these techniques have contributed to our understanding of pre-implantation and early post-implantation development and of in vitro pluripotency. Finally, we overview the current challenges facing single-cell research and highlight the latest advances and potential future avenues.

Indexed as

AnimalsCell DifferentiationEmbryo, MammalianEmbryonic DevelopmentHumansTranscription, GeneticTranscriptome

Identifiers

What OpenQuestion holds

Textmetadata
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.