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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. 
Graded and Abrupt Responses
Some signaling systems generate...
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Cell Signaling Feedback Loops

Positive and negative feedback loops are crucial for regulating biological signaling systems. These feedback loops are processes that connect output signals to their inputs.
Negative feedback loops
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Output limiter
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Transient and Steady-state Response

In control systems, test signals are essential for evaluating performance under various conditions. The ramp function is effective for systems undergoing gradual changes, while the step function is suitable for assessing systems facing sudden disturbances. For systems subjected to shock inputs, the impulse function is the most appropriate test signal.
These test signals are integral in designing control systems to exhibit two key performance aspects: transient response and steady-state response.

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Simulating quantitative cellular responses using asynchronous threshold Boolean network ensembles.

John Jack1, John F Wambaugh, Imran Shah

  • 1National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA.

BMC Systems Biology
|July 13, 2011
PubMed
Summary
This summary is machine-generated.

This study models cell signaling to predict tissue responses to chemicals. The approach uses Boolean networks to simulate cell populations, showing reproducible results consistent with experimental data for toxicity prediction.

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Area of Science:

  • Computational biology
  • Systems biology
  • Toxicology

Background:

  • Predicting biological system responses to perturbations is crucial.
  • Tissue heterogeneity complicates chemical toxicity assessments.
  • A novel model aggregates individual cell behaviors to estimate tissue-level responses.

Purpose of the Study:

  • To develop a biologically motivated model for estimating tissue-level responses.
  • To investigate the aggregation of individual cell behaviors for predicting physiological effects.
  • To assess the model's ability to predict toxicity and cellular responses.

Main Methods:

  • Developed an asynchronous threshold Boolean network simulation algorithm for single-cell signal transduction.
  • Utilized ensembles of these models to estimate population-level responses.
  • Derived a crosstalk network of growth factors and cytokines for cell proliferation signaling.

Main Results:

  • The Boolean network ensembles demonstrated reproducible aggregate responses.
  • Simulation results were compared to experimental observations in hepatocytes.
  • The model showed biologically plausible noisy individual cellular responses with reproducible mean behavior.

Conclusions:

  • Boolean network ensembles with asynchronous updating yield plausible cellular responses and reproducible population behavior.
  • The model can estimate responses to varying extracellular ligand concentrations.
  • This quantitative and extensible approach aids in understanding contaminant effects on tissues.