Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

CellCommuNet

General information

URL: http://www.inbirg.com/cellcommunet
Full name: cell–cell communication networks
Description: CellCommuNet has been constructed to present the results of cell-cell communication analysis in various diseases, encompassing 376 scRNAseq datasets with over 4,300,000 cell transcriptomics that include healthy samples and a wide range of diseases.
Year founded: 2024
Last update:
Version: v1.0
Accessibility:
Accessible
Country/Region: China

Classification & Tag

Data type:
Data object:
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Contact information

University/Institution: Chongqing Medical University
Address:
City: Chongqing
Province/State:
Country/Region: China
Contact name (PI/Team): Jianbo Pan
Contact email (PI/Helpdesk): panjianbo@cqmu.edu.cn

Publications

37850657
CellCommuNet: an atlas of cell-cell communication networks from single-cell RNA sequencing of human and mouse tissues in normal and disease states. [PMID: 37850657]
Ma Q, Li Q, Zheng X, Pan J.

Cell-cell communication, as a basic feature of multicellular organisms, is crucial for maintaining the biological functions and microenvironmental homeostasis of cells, organs, and whole organisms. Alterations in cell-cell communication contribute to many diseases, including cancers. Single-cell RNA sequencing (scRNA-seq) provides a powerful method for studying cell-cell communication by enabling the analysis of ligand-receptor interactions. Here, we introduce CellCommuNet (http://www.inbirg.com/cellcommunet/), a comprehensive data resource for exploring cell-cell communication networks in scRNA-seq data from human and mouse tissues in normal and disease states. CellCommuNet currently includes 376 single datasets from multiple sources, and 118 comparison datasets between disease and normal samples originating from the same study. CellCommuNet provides information on the strength of communication between cells and related signalling pathways and facilitates the exploration of differences in cell-cell communication between healthy and disease states. Users can also search for specific signalling pathways, ligand-receptor pairs, and cell types of interest. CellCommuNet provides interactive graphics illustrating cell-cell communication in different states, enabling differential analysis of communication strength between disease and control samples. This comprehensive database aims to be a valuable resource for biologists studying cell-cell communication networks.

Nucleic Acids Res. 2024:52(D1) | 14 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
1293/6895 (81.262%)
Interaction:
260/1194 (78.308%)
Pathway:
75/451 (83.592%)
Health and medicine:
309/1738 (82.278%)
1293
Total Rank
11
Citations
11
z-index

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Record metadata

Created on: 2024-07-16
Curated by:
Miaomiao Wang [2024-08-24]
shaosen zhang [2024-07-23]
shaosen zhang [2024-07-19]
zheng luo [2024-07-16]