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Overview of Cell Signaling01:23

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Despite the protective membrane that separates a cell from the environment, cells need the ability to detect and respond to environmental changes. Additionally, cells often need to communicate with one another. Unicellular and multicellular organisms use a variety of cell signaling mechanisms to communicate with the environment.
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Hormones—or any molecule that binds to a receptor, known as a ligand—that are lipid-insoluble (water-soluble) are not able to diffuse across the cell membrane. In order to be able to affect a cell without entering it, these hormones bind to receptors on the cell membrane. When a first messenger, a hormone, binds to a receptor, a signal cascade is set off, causing second messengers, proteins inside the cell, to become activated, resulting in downstream effects.
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Once a ligand binds to a receptor, the signal is transmitted through the membrane and into the cytoplasm. The continuation of a signal in this manner is called signal transduction. Signal transduction only occurs with cell-surface receptors, which cannot interact with most components of the cell, such as DNA. Only internal receptors can interact directly with DNA in the nucleus to initiate protein synthesis. When a ligand binds to its receptor, conformational changes occur that affect the...
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Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo
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COMUNET: a tool to explore and visualize intercellular communication.

Maria Solovey1,2,3, Antonio Scialdone1,2,3

  • 1Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg 85764, Germany.

Bioinformatics (Oxford, England)
|May 14, 2020
PubMed
Summary
This summary is machine-generated.

We developed Cell cOmmunication exploration with MUltiplex NETworks (COMUNET), a tool that simplifies interpreting cell-cell communication from single-cell data. COMUNET visualizes communication patterns, aiding analysis in biological conditions like development and disease.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Intercellular communication is vital for multicellular organisms.
  • Existing algorithms for analyzing single-cell RNA sequencing (scRNA-seq) data on cell-cell communication often yield results that are difficult to visualize and interpret.

Purpose of the Study:

  • To develop a user-friendly tool, COMUNET, for streamlining the interpretation of cell-cell communication analyses from scRNA-seq data.
  • To enable visualization and exploration of complex communication patterns between cell types using multiplex networks.

Main Methods:

  • COMUNET utilizes multiplex networks to represent and cluster potential cell-cell communication patterns.
  • The tool facilitates searching for specific communication patterns and conducting comparative analyses between different biological conditions.
  • Implemented as an R package for accessibility and reproducibility.

Main Results:

  • COMUNET successfully visualizes and interprets cell-cell communication networks.
  • Applied to mouse embryo and acute myeloid leukemia datasets, revealing distinct communication patterns.
  • Demonstrated utility in comparing communication profiles at diagnosis versus post-treatment in leukemia.

Conclusions:

  • COMUNET provides an effective solution for interpreting complex cell-cell communication data from scRNA-seq.
  • The multiplex network approach offers a powerful framework for understanding cellular interactions in development and disease.
  • The R package facilitates broader adoption and application of these analytical methods in biological research.