Evidence map›Paper›PMID 31932320›Full record

ReviewCold Spring Harbor perspectives in biology2020

Advancing Stem Cell Research through Multimodal Single-Cell Analysis.

Iwo Kucinski, Berthold Gottgens

Abstract readReview
In one paragraph

Review in Cold Spring Harbor perspectives in biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Single-cell Technology in Stem Cell Research.Current stem cell research & therapy · 2025
    Review
  4. Article
  5. Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Review
  6. Article
  7. Article
  8. Review
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

2 authors.

Iwo KucinskiWellcome-MRC Cambridge Stem Cell Institute and Department of Haematology, University of Cambridge, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge CB2 0AW, United Kingdom.
Berthold GottgensWellcome-MRC Cambridge Stem Cell Institute and Department of Haematology, University of Cambridge, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge CB2 0AW, United Kingdom.

Funding

VISION: ValIdated Systematic IntegratiON of epigenomic dataR24DK106766 · NIDDK · PENNSYLVANIA STATE UNIVERSITY, THE · PI BLOBEL, GERD A, BODINE, DAVID M. · 2016 to 2020
$6.2M
Cancer Research UK 21762Medical Research Council MC_PC_12009Medical Research Council MC_PC_17230Medical Research Council MR/S036113/1NIDDK NIH HHS R24 DK106766Wellcome Trust 206328/Z/17/Z
6 · The paper itself

Abstract

Technological advances play a key role in furthering our understanding of stem cell biology, and advancing the prospects of regenerative therapies. Highly parallelized methods, developed in the last decade, can profile DNA, RNA, or proteins in thousands of cells and even capture data across two or more modalities (multiomics). This allows unbiased and precise definition of molecular cell states, thus allowing classification of cell types, tracking of differentiation trajectories, and discovery of underlying mechanisms. Despite being based on destructive techniques, novel experimental and bioinformatic approaches enable embedding and extraction of temporal information, which is essential for deconvolution of complex data and establishing cause and effect relationships. Here, we provide an overview of recent studies pertinent to stem cell biology, followed by an outlook on how further advances in single-cell molecular profiling and computational analysis have the potential to shape the future of both basic and translational research.

Indexed as

Stem Cell ResearchAnimalsCell DifferentiationComputational BiologyHumansModels, BiologicalMusclesNeuronsSingle-Cell AnalysisStem Cells

Identifiers

PMID31932320
PMCPMC7328456

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.