2026· Methods in molecular biology· Vol 3058, pp.
243-259
· 0 citations
Medicine
TL;DR
The current landscape of CCC studies is introduced, emphasizing how ST data provide spatially resolved insights, and the integration of novel algorithms to enhance CCC inference are discussed.
This review examines recent methodological developments in CCC inference from ST data, focusing on how statistical, optimal transport, and deep learning frameworks incorporate spatial information to model ligand–receptor interactions and downstream signaling.
Yue-Song Wu, Hao-Hao Su, Yue-Hua Cui· Briefings in Bioinformatics· 0 citations
Cell-cell communication (CCC) is involved in regulating cellular behavior in tissues. Spatial transcriptomics adds local context to gene expression, enabling more biologically grounded CCC inference than single-cell RNA-seq alone. Rapid method development has yielded diverse CCC methods, each addressing distinct biolog...
Zlatka Fischer, Katharina Imkeller, Marcel H. Schulz et al.· Trends in Genetics· 2 citations
This manuscript explores the current landscape of single-cell RNA sequencing (scRNA-seq), highlighting key studies that have leveraged this technology to advance biological understanding for clinical purposes through the construction of gene regulatory networks (GRNs) from single-cell transcriptomic data.
J. López-Castiblanco, L. López-Kleine, Yesid Cuesta-Astroz· Journal of Investigative Med...· 0 citations
Cell-cell communication modulates cell fate decisions by relaying information across tissues and inducing intracellular responses mediated by gene regulatory networks. Although the inference of cell-cell communication from high-throughput data is gaining popularity, studying how communication pathways operate across bi...
F. Bocci, Yunlong Y. Jia, Scott Atwood et al.· Cell Systems· 0 citations
A "cellular spatiotemporal dogma" governs the zygote's programmed development into a complete plant and its adaptation to various environmental stresses, representing the set of principles describing how gene expression, cell identity, and function are coordinated across physical spatial contexts and temporal developme...
This study introduces CellART, a unified framework designed to extract single-cell information across diverse high-resolution spatial transcriptomics platforms, including VisiumHD, Xenium, MERFISH, and Stereo-seq, and highlights its ability to fully leverage high-resolution ST data.
Yu-Heng Chen, Yu-Yao Liu, Zhi-Wei Wang et al.· bioRxiv· 1 citation
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