ArticleCurrent opinion in systems biology2021
The landscape of cell-cell communication through single-cell transcriptomics.
Article in Current opinion in systems biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers.
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Who cites it
137 citing papers in PubMed.
- Article
- Multi-omic analysis of jaw-bone periosteum identifies the role of macrophage-derived SPP1 in CtskBone research · 2026Article
- Single-Cell Transcriptomics of Pyrimidine Salvage in HBV-Related HCC Reveals Prognostic and Immune Infiltration Features.Biomolecules & therapeutics · 2026Article
- Airway cell-cell communication in smoking through integration of spatial and single-cell transcriptomics.Respiratory research · 2026Article
- Integrating short-read and long-read single-cell transcriptomics of pig pituitary reveals mechanisms of high-altitude hypoxia adaptation.PLoS genetics · 2026Article
- Article
- T Cell-Macrophage Interactions Influence Chemotherapeutic Response in Ovarian Cancer Patients.International journal of molecular sciences · 2026Article
- Variational sparse Gaussian-process method for detecting spatially variable genes and cellular interactions in spatial transcriptomics.Briefings in bioinformatics · 2026Article
- Spatial co-expression and cell-cell communication inference from spatially resolved transcriptomics with CONCISE.bioRxiv : the preprint server for biology · 2026Article
- Inference of spatial chromatin accessibility via integration of spatial transcriptomics and single-cell multi-omics data.Nature communications · 2026Article
- CytoSignal detects locations and dynamics of ligand-receptor signaling at cellular resolution from spatial transcriptomic data.Nature genetics · 2026Article
- Network-Based Bioinformatics Reveal Microenvironment-Driven Cell-to-Cell Communication in the Progression of Multiple Myeloma.International journal of molecular sciences · 2026Article
- Charting spatial ligand-target activity using Renoir.Nature communications · 2026Article
- Robust identification of cell-cell communication heterogeneity in single cells.bioRxiv : the preprint server for biology · 2026Article
- Benchmarking tools for deciphering cellular crosstalk in spatially-resolved transcriptomics.Genome biology · 2026Article
- spRefine denoises and imputes spatial transcriptomic data with a reference-free framework powered by genomic language model.Genome research · 2026Article
- scComm: a contrastive learning framework for deciphering cell-cell communications at single-cell resolution.Genome biology · 2026Article
- Predictive modeling of molecular activity underlying physical cell-cell interactions.Cell reports methods · 2026Article
- Decoding the archipelago: single-cell biomarkers rechart the molecular geography of acute myeloid leukemia.Cell communication and signaling : CCS · 2026Review
- Tensor-cell2cell v2 unravels coordinated dynamics of protein- and metabolite-mediated cell-cell communication.Bioinformatics (Oxford, England) · 2026Article
77 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Cell-cell communication is a fundamental process that shapes biological tissue. Historically, studies of cell-cell communication have been feasible for one or two cell types and a few genes. With the emergence of single-cell transcriptomics, we are now able to examine the genetic profiles of individual cells at unprecedented scale and depth. The availability of such data presents an exciting opportunity to construct a more comprehensive description of cell-cell communication. This review discusses the recent explosion of methods that have been developed to infer cell-cell communication from non-spatial and spatial single-cell transcriptomics, two promising technologies which have complementary strengths and limitations. We propose several avenues to propel this rapidly expanding field forward in meaningful ways.
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Registered trials
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.