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Related Concept Videos

Diversity in Cell Signaling Responses01:22

Diversity in Cell Signaling Responses

The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
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Some signaling systems generate...
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
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Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
Amplifying Signals via Enzymatic Cascade01:22

Amplifying Signals via Enzymatic Cascade

When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze the...
Intracellular Signaling Cascades01:24

Intracellular Signaling Cascades

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...
Intracellular Signaling Cascades01:24

Intracellular Signaling Cascades

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...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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Published on: October 19, 2021

Dynamic deterministic effects propagation networks: learning signalling pathways from longitudinal protein array

Christian Bender1, Frauke Henjes, Holger Fröhlich

  • 1Department of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. c.bender@dkfz.de

Bioinformatics (Oxford, England)
|September 9, 2010
PubMed
Summary
This summary is machine-generated.

We developed a new method to reconstruct signaling networks from time-course data, improving cancer research and drug development. This approach accurately identifies known signaling cascades in breast cancer cells.

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Last Updated: Jun 9, 2026

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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Area of Science:

  • Systems Biology
  • Cancer Research
  • Molecular Interactions

Background:

  • Network modeling is crucial for understanding protein interactions in cancer.
  • Reconstructing signaling pathways aids in identifying therapeutic targets.
  • This study focuses on de novo reconstruction from time-course data.

Purpose of the Study:

  • To present a novel method for reconstructing signaling networks from time-course experiments.
  • To apply the method to phosphorylated protein abundance data from a human breast cancer cell line.
  • To demonstrate the method's ability to unravel protein interactions and identify pathway aberrations.

Main Methods:

  • Modeling signaling dynamics using active/passive protein states over time.
  • Employing a fixed signal propagation scheme and likelihood score for network evaluation.
  • Utilizing a hidden Markov model and genetic algorithm for network structure optimization.

Main Results:

  • The proposed method outperforms existing dynamical Bayesian network approaches.
  • Successfully identified known signaling cascades within the ERBB pathway using real breast cancer data.
  • Demonstrated effective reconstruction of signaling networks from experimental data.

Conclusions:

  • The novel method provides a robust approach for signaling network reconstruction.
  • This technique enhances the understanding of cellular regulatory programs in cancer.
  • The developed tool is available in the R programming language for broader application.