Evidence map›Paper›PMID 33168968›Full record

ReviewNature reviews. Genetics2021

Deciphering cell-cell interactions and communication from gene expression.

Erick Armingol, Adam Officer, Olivier Harismendy, Nathan E Lewis

Open access · bronzeAbstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 768 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
768citing papers in PubMed, 1 pooled it
52.3field-weighted citation impact, top 1% of its field
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

768 citing papers in PubMed, 1 synthesis or guideline pooled it, 1,257 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
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  5. Review
  6. Review
  7. Review
  8. Review
  9. iScience · 2026
    Article
  10. Article
  11. Review
  12. Article
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  14. Article
  15. Cellular transcriptomic signatures underpinning the heterogeneity of depression in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

708 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 at 3 institutions in 2 countries.

Erick Armingol *Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0002-1546-9165
Adam Officer *Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0003-2913-6051
Olivier HarismendyDivision of Biomedical Informatics, University of California, San Diego, La Jolla, CA, USA. oharismendy@ucsd.edu.ORCID http://orcid.org/0000-0002-8098-9888
Nathan E LewisDepartment of Pediatrics, University of California, San Diego, La Jolla, CA, USA. nlewisres@ucsd.edu.
University of California San Diego · USFoundation Center · USNovo Nordisk Foundation · DK

Funding

San Diego Biomedical Informatics Education & Research (SABER)T15LM011271 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SHAMIM NEMATI · 2012 to 2026
$9.7M
Elucidating the molecular and contextual basis for IDLE ultralow risk lesions and the tumor immune microenvironment of high risk in situ and invasive breast cancersU01CA196406 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BOROWSKY, ALEXANDER D, ESSERMAN, LAURA J · 2015 to 2020
$5.8M
Unraveling the mammalian secretory pathway through systems biology and algorithm developmentR35GM119850 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LEWIS, NATHAN ENOCH · 2016 to 2025
$4.3M
NCI NIH HHS U01 CA196406NIGMS NIH HHS R35 GM119850NLM NIH HHS T15 LM011271
6 · The paper itself

Abstract

Cell-cell interactions orchestrate organismal development, homeostasis and single-cell functions. When cells do not properly interact or improperly decode molecular messages, disease ensues. Thus, the identification and quantification of intercellular signalling pathways has become a common analysis performed across diverse disciplines. The expansion of protein-protein interaction databases and recent advances in RNA sequencing technologies have enabled routine analyses of intercellular signalling from gene expression measurements of bulk and single-cell data sets. In particular, ligand-receptor pairs can be used to infer intercellular communication from the coordinated expression of their cognate genes. In this Review, we highlight discoveries enabled by analyses of cell-cell interactions from transcriptomic data and review the methods and tools used in this context.

Indexed as

Cell CommunicationGene ExpressionAnimalsComputational BiologyGene Expression ProfilingHomeostasisHumansImmunityProtein BindingRNA-Seq

Identifiers

PMID33168968
PMCPMC7649713
OpenAlexW3099810371

What Socratic 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 Socratic graph.