AIMC Topic: Cell Communication

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SpatialFusion: A Unified Model for Integrating Spatial Transcriptomics to Unveil Cell-type Distribution, Interaction, and Functional Heterogeneity in Tissue Microenvironments.

Journal of molecular biology
Recent advances in spatial transcriptomics (ST) have significantly enhanced our understanding of tissue structure and intercellular interactions. However, existing methods for spatial domain identification and cell type deconvolution still face chall...

Ligand-receptor interaction profiling as a predictive biomarker for anti-PD-1 therapy response in melanoma.

Clinical and experimental medicine
Cell-to-cell communication through ligand-receptor (LR) interactions can fundamentally shape the tumor microenvironment and immune responses, but the full spectrum of these interactions in anti-PD-1 therapy remains unexplored. We developed a predicti...

GraphComm predicts cell cell communication using a graph based deep learning method in single cell RNA sequencing data.

Scientific reports
Interactions between cells coordinate various functions across cell-types in health and disease states. Novel single-cell techniques enable deep investigation of cellular crosstalk at single-cell resolution. Cell-cell communication (CCC) is mediated ...

Dissecting crosstalk induced by cell-cell communication using single-cell transcriptomic data.

Nature communications
During cell-cell communication (CCC), pathways activated by different ligand-receptor pairs may have crosstalk with each other. While multiple methods have been developed to infer CCC networks and their downstream response using single-cell RNA-seq d...

Insight into microbial extracellular vesicles as key communication materials and their clinical implications for lung cancer (Review).

International journal of molecular medicine
The complexity of lung cancer, driven by multifactorial causes such as genetic, environmental and lifestyle factors, underscores the necessity for tailored treatment strategies informed by recent advancements. Studies highlight a significant associat...

Prediction of Ligand-Receptor Interactions Based on CatBoost and Deep Forest and Their Application in Cell-Cell Communication Analysis.

Journal of chemical information and modeling
Cell-to-cell communication (CCC) is prominent for cell growth and development as well as tissue and organ formation. CCC inference can help us to deeply understand cellular interplay and discover potential therapeutic targets for complex diseases. Ce...

SIMVI disentangles intrinsic and spatial-induced cellular states in spatial omics data.

Nature communications
Spatial omics technologies enable analysis of gene expression and interaction dynamics in relation to tissue structure and function. However, existing computational methods may not properly distinguish cellular intrinsic variability and intercellular...

The Role of Autophagy and Cell Communication in COPD Progression: Insights from Bioinformatics and scRNA-seq.

COPD
Chronic obstructive pulmonary disease (COPD) is characterized by restricted airflow that leads to significant respiratory difficulties. This progressive disease often results in diminished pulmonary function and the onset of additional respiratory co...

Spatially Informed Graph Structure Learning Extracts Insights from Spatial Transcriptomics.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Embeddings derived from cell graphs hold significant potential for exploring spatial transcriptomics (ST) datasets. Nevertheless, existing methodologies rely on a graph structure defined by spatial proximity, which inadequately represents the diversi...

Collection of microrobots for gentle cell manipulation.

Science robotics
Optically actuated soft microrobotic tools were designed for cell transportation, manipulation, and cell-to-cell interactions.