Evidence map›Paper›PMID 28109325›Full record

ReviewJournal of hematology & oncology2017

Studying hematopoiesis using single-cell technologies.

Fang Ye, Wentao Huang, Guoji Guo

Abstract readReview
In one paragraph

Review in Journal of hematology & oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Review
  2. FACS-Based Assessment of Human Hematopoietic Stem and Progenitor Cells.International journal of molecular sciences · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Comparative analysis between highFrontiers in oncology · 2023
    Article
  9. Article
  10. Review
  11. Article
  12. Magnetophoretic Decoupler for Disaggregation and Interparticle Distance Control.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

3 authors.

Fang YeCenter for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Wentao HuangCenter for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Guoji GuoCenter for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China. ggj@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hematopoiesis is probably the best-understood stem cell differentiation system; hematopoietic stem cell (HSC) transplantation represents the most widely used regenerative therapy. The classical view of lineage hierarchy in hematopoiesis is built on cell type definition system by a group of cell surface markers. However, the traditional model is facing increasing challenges, as many classical cell types are proved to be heterogeneous. Recently, the developments of new technologies allow genome, transcriptome, proteome, and epigenome analysis at the single-cell level. For the first time, we can study hematopoietic system at single-cell resolution on a multi-omic scale. Here, we review recent technical advances in single-cell analysis technology, as well as their current applications. We will also discuss the impact of single-cell technologies on both basic research and clinical application in hematology.

Indexed as

HematopoiesisAnimalsGenomicsHumansProteomicsSingle-Cell AnalysisHematopoietic stem cellLineage hierarchyRegulatory networkSingle-cell analysis

Identifiers

PMID28109325
PMCPMC5251333

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.