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Related Concept Videos

Signal Transduction: Overview01:26

Signal Transduction: Overview

Cells respond to many types of information, often through receptor proteins positioned on the membrane. They respond to chemical signals, such as hormones, neurotransmitters, and other signaling molecules, initiating a series of molecular reactions to produce an appropriate response. This is called signal transduction. Cells also coordinate different responses elicited by the same signaling molecule via mediators, allowing molecular cross-talk.
Typically, signal transduction involves three...
Cell Signaling Feedback Loops01:07

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
Most signaling systems have negative feedback loops that can perform different functions such as output limiter, and adaptation.
Output limiter
Upon receiving an input signal, the cellular response rapidly increases until a threshold is reached. Beyond this threshold, a negative feedback loop...
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...
Chemical Signaling in the Endocrine System01:08

Chemical Signaling in the Endocrine System

A signaling cascade is a series of events that facilitates the transmission of information within or between cells, culminating in a targeted response in the recipient cell. As chemical messengers, hormones are pivotal in initiating and modulating these intricate signaling cascades based on their solubility.
Lipid-soluble hormones, such as steroid hormones, demonstrate an intracellular action. These hormones traverse cell membranes due to their lipid nature. Once inside the target cell, they...
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...

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Related Experiment Video

Updated: Jun 19, 2026

Mimicking the Function of Signaling Proteins: Toward Artificial Signal Transduction Therapy
12:24

Mimicking the Function of Signaling Proteins: Toward Artificial Signal Transduction Therapy

Published on: September 29, 2016

The ABC of reverse engineering biological signalling systems.

Maria Secrier1, Tina Toni, Michael P H Stumpf

  • 1Centre for Bioinformatics, Imperial College London, UK.

Molecular Biosystems
|October 3, 2009
PubMed
Summary

Estimating parameters for biological models is challenging due to unknown values. Approximate Bayesian Computation (ABC) helps infer these parameters and their uncertainty, improving systems biology insights.

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Statistical Inference

Background:

  • Accurate biological system modeling requires knowledge of model structure and dynamic parameters.
  • Parameter values are frequently unknown or impossible to measure directly for most biological processes.
  • Parameter estimation from observed data is crucial but introduces uncertainty.

Purpose of the Study:

  • To highlight the importance of quantifying uncertainty in parameter estimates for biological models.
  • To introduce and explain Approximate Bayesian Computation (ABC) as a statistical approach for parameter inference.
  • To demonstrate how ABC can provide deeper insights into biological system dynamics.

Main Methods:

  • Utilizing Approximate Bayesian Computation (ABC) to approximate posterior distributions of model parameters.
  • Analyzing the posterior distribution of parameters to understand system dynamics.
  • Applying the ABC approach to a mitogen-activated protein kinase (MAPK) phosphorylation cascade model.

Main Results:

  • ABC successfully approximates posterior distributions for model parameters.
  • The analysis of posterior distributions offers valuable insights into system dynamics.
  • The study illustrates the application of ABC in the context of a specific biological pathway (MAPK cascade).

Conclusions:

  • Appreciating and quantifying parameter uncertainty is vital in systems biology.
  • Approximate Bayesian Computation (ABC) is an effective statistical method for parameter inference and uncertainty quantification.
  • Analyzing parameter distributions, rather than point estimates, is beneficial for understanding 'sloppy models' in systems biology.