Evidence map›Paper›PMID 34217372›Full record

ReviewCell & bioscience2021

Applications and analytical tools of cell communication based on ligand-receptor interactions at single cell level.

Fen Ma, Siwei Zhang, Lianhao Song, Bozhi Wang, Lanlan Wei, Fengmin Zhang

Open access · goldAbstract readReview
In one paragraph

Review in Cell & bioscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

28 citing papers in PubMed, 40 citations in OpenAlex.

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  18. CCIDB: a manually curated cell-cell interaction database with cell context information.Database : the journal of biological databases and curation · 2023
    Article
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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

6 authors at 1 institution in 1 country.

Fen MaDepartment of Microbiology, Harbin Medical University, Harbin, 150081, China.
Siwei ZhangDepartment of Microbiology, Harbin Medical University, Harbin, 150081, China.
Lianhao SongDepartment of Microbiology, Harbin Medical University, Harbin, 150081, China.
Bozhi WangDepartment of Microbiology, Harbin Medical University, Harbin, 150081, China.
Lanlan WeiDepartment of Microbiology, Harbin Medical University, Harbin, 150081, China. 2743623823@qq.com.
Fengmin ZhangDepartment of Microbiology, Harbin Medical University, Harbin, 150081, China. fengminzhang@ems.hrbmu.edu.cn.ORCID http://orcid.org/0000-0002-5177-1927
Harbin Medical University · CN

Funding

National Natural Science Foundation of China 81672670National Natural Science Foundation of China 81773267
6 · The paper itself

Abstract

backgroundCellular communication is an essential feature of multicellular organisms. Binding of ligands to their homologous receptors, which activate specific cell signaling pathways, is a basic type of cellular communication and intimately linked to many degeneration processes leading to diseases. MAIN BODY: This study reviewed the history of ligand-receptor and presents the databases which store ligand-receptor pairs. The recently applications and research tools of ligand-receptor interactions for cell communication at single cell level by using single cell RNA sequencing have been sorted out.

conclusionThe summary of the advantages and disadvantages of analysis tools will greatly help researchers analyze cell communication at the single cell level. Learning cell communication based on ligand-receptor interactions by single cell RNA sequencing gives way to developing new target drugs and personalizing treatment.

Indexed as

Cell communicationLigand-receptor interactionsSingle cell RNA sequencingTarget therapyTumor microenvironment

Identifiers

PMID34217372
PMCPMC8254218
OpenAlexW3180289141

What Socratic 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 Socratic graph.