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Related Concept Videos

Overview of Cell Signaling01:23

Overview of Cell Signaling

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.
Cells respond to many types of information, often through receptor proteins positioned on the membrane. For example, skin cells respond to and transmit touch...
Overview of Cell Signaling01:23

Overview of Cell Signaling

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.
Cells respond to many types of information, often through receptor proteins positioned on the membrane. For example, skin cells respond to and transmit touch...
What is Cell Signaling?02:03

What is Cell Signaling?

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 to respond to the environment.
What is Cell Signaling?02:03

What is Cell Signaling?

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 to respond to the environment.
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...
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...

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Identification of Intracellular Signaling Events Induced in Viable Cells by Interaction with Neighboring Cells Undergoing Apoptotic Cell Death
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Published on: December 27, 2016

Cellular signaling identifiability analysis: a case study.

Ryan T Roper1, Maria Pia Saccomani, Paolo Vicini

  • 1Resource Facility for Population Kinetics, Department of Bioengineering Box 355061, University of Washington, Seattle, WA 98195-5061, United States. rtroper@u.washington.edu

Journal of Theoretical Biology
|March 2, 2010
PubMed
Summary
This summary is machine-generated.

Mathematical modeling in cell biology faces parameter identifiability challenges. This study reveals which parameters are impossible to estimate even with perfect data, highlighting an under-appreciated issue in biological modeling.

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Area of Science:

  • Cell Biology
  • Systems Biology
  • Mathematical Biology

Background:

  • Mathematical modeling is crucial in cell biology for simulation and parameter estimation.
  • Parameter estimation is less common than simulation, especially for cellular signaling.
  • Limited data availability hinders parameter estimation in complex biological models.

Purpose of the Study:

  • To investigate global parameter identifiability in cellular signaling models.
  • To determine which model parameters are theoretically unestimatable, even with ideal data.
  • To highlight the under-appreciated challenges of parameter identifiability in cell biology.

Main Methods:

  • Utilized published cellular signaling models.
  • Performed global parameter identifiability analysis.
  • Employed DAISY (Differential Algebra for the Identifiability of SYstems) software.

Main Results:

  • Identified specific parameters that are impossible to estimate.
  • Demonstrated theoretical limitations in parameter estimation for ODE models.
  • Highlighted issues with parameter identifiability in ordinary differential equation (ODE) models.

Conclusions:

  • Parameter identifiability is a critical, under-appreciated issue in cell biology modeling.
  • DAISY analysis can reveal fundamental limitations in model parameter estimation.
  • Further attention to identifiability is needed for robust biological modeling.