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Related Concept Videos

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...
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.
Convergence and divergence, and cross-talk between signaling pathways
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...
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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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. 
Graded and Abrupt Responses
Some signaling systems generate...

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A Web Tool for Generating High Quality Machine-readable Biological Pathways
08:01

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

Biological pathways as communicating computer systems.

Marta Z Kwiatkowska1, John K Heath

  • 1Oxford University Computing Laboratory, Oxford, UK.

Journal of Cell Science
|August 7, 2009
PubMed
Summary
This summary is machine-generated.

Researchers developed a computational method to analyze complex biological pathways, reducing experimental time and cost. This approach models biological processes as executable programs, identifying key experiments for understanding cell signaling.

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Cell Signaling

Background:

  • Dissecting complex biological pathways requires extensive experimentation, which is time-consuming and costly.
  • A need exists for automated methods to analyze biological pathways and prioritize experiments.
  • Existing computational tools for analyzing reactive communicating systems are underutilized in biology.

Purpose of the Study:

  • To present a novel computational method for analyzing biological pathways.
  • To demonstrate how this method can automate the identification of critical experiments.
  • To explore the application of software analysis techniques in cell biology.

Main Methods:

  • Biological pathways are formulated as executable computer programs.
  • Computational tools, originally developed for analyzing reactive communicating systems, are employed.
  • Methods for analyzing complex software systems are adapted for biological pathway interrogation.

Main Results:

  • The computational approach was applied to Fibroblast Growth Factor (FGF), Mitogen-Activated Protein Kinase (MAPK), and Delta/Notch signaling pathways.
  • The method yielded significant insights into the behavior of these signaling pathways.
  • These computational findings were subsequently validated by experimental data.

Conclusions:

  • Computational modeling offers an efficient way to analyze complex biological pathways.
  • This approach can significantly reduce the time and resources needed for biological research.
  • The integration of software analysis techniques holds promise for advancing cell biology.