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Circadian Rhythms and Gene Regulation

Circadian Rhythms and Gene Regulation

The biological clock is involved in many aspects of regulating complex physiology in all animals. It was in 1935 when German zoologists, Hans Kalmus and Erwin Bünning, discovered the existence of circadian rhythm in Drosophila melanogaster. However, the internal molecular mechanisms behind the circadian clock remained a mystery until 1984, when Jeffrey C. Hall, Michael Rosbash, and Michael W. Young discovered the expression of the Per gene oscillating over a 24-hour cycle. In subsequent years,...

Circadian Rhythms and Gene Regulation

Circadian Rhythms and Gene Regulation

The biological clock is involved in many aspects of regulating complex physiology in all animals. It was in 1935 when German zoologists, Hans Kalmus and Erwin Bünning, discovered the existence of circadian rhythm in Drosophila melanogaster. However, the internal molecular mechanisms behind the circadian clock remained a mystery until 1984, when Jeffrey C. Hall, Michael Rosbash, and Michael W. Young discovered the expression of the Per gene oscillating over a 24-hour cycle. In subsequent years,...

Cell Signaling Feedback Loops

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.
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Regulation of Expression at Multiple Steps

Regulation of Expression at Multiple Steps

The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the addition of a...

Regulation of Expression Occurs at Multiple Steps

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...

Regulation of Expression Occurs at Multiple Steps

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...

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Related Experiment Video

Updated: Jun 24, 2026

A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression

A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression

Published on: October 6, 2019

Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit.

O Eriksson¹, B Brinne, Y Zhou

¹Stockholm University, Stockholm Bioinformatics Center, AlbaNova, Stockholm, Sweden.

IET Systems Biology

|March 19, 2009

Summary

Researchers simplified complex protein networks to understand cell cycle dynamics. This new method reveals how system parameters control stability, offering insights into molecular network regulation.

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Area of Science:

Computational Biology
Systems Biology
Molecular Network Dynamics

Background:

Molecular networks of genes and proteins exhibit complex regulatory dynamics.
Analyzing these networks often requires extensive simulations or graphical methods.
Understanding the governing principles of complex biological networks remains challenging.

Purpose of the Study:

To develop a method for directly detecting dynamical regularities in complex molecular networks.
To analyze the governing principles of periodic oscillations in protein-protein interaction networks.
To derive explicit conditions for system stability in biological regulatory circuits.

Main Methods:

Exploited simplifying biological conditions to reduce model complexity.
Utilized a 'tearing-and-zooming' approach to create a piecewise linear system.
Identified functional subsystems as 'dynamical modules' acting as sensitive switches.
Derived explicit conditions for cell cycle dynamics and system stability.

Main Results:

Reduced a complex protein-protein network model to a two-variable piecewise linear system.
Identified dynamical modules that capture essential network functions.
Derived explicit conditions demonstrating how cell cycle dynamics depend on system parameters.
Proved global conditions for system stability for the first time.

Conclusions:

The developed approach simplifies the analysis of complex biological regulatory circuits.
This method provides direct insights into network dynamics and stability.
The approach is potentially applicable to other well-characterized biological regulatory networks.