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Related Concept Videos

Combinatorial Gene Control02:33

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
Structure of a Gene01:30

Structure of a Gene

A gene is the fundamental unit of heredity. Every individual has two copies of each gene, one inherited from each parent. Although most people contain the same genes, there is a small fraction that is slightly different amongst people. A gene with a small difference in its sequence of DNA bases forms different alleles, contributing to different phenotypes.
However, only 1% of the DNA is composed of genes that encode proteins; the rest, 99% is non-coding DNA. This non-coding DNA performs...
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
Organization of Genes02:07

Organization of Genes

Overview
Genome Copying Errors02:46

Genome Copying Errors

DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger their  survival. Therefore, the copying errors are checked and repaired at three levels.

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Related Experiment Video

Updated: Jun 17, 2026

Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins
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Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins

Published on: October 18, 2022

Computational limits to binary genes.

Nicolae Radu Zabet1, Dominique F Chu

  • 1School of Computing, University of Kent, Canterbury CT2 7NF, UK. n.r.zabet@kent.ac.uk

Journal of the Royal Society, Interface
|December 17, 2009
PubMed
Summary
This summary is machine-generated.

Gene expression systems face a trade-off between speed, noise, and metabolic cost. Optimal systems minimize noise and maximize speed for a given cost, with leak-free designs being superior.

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Area of Science:

  • Systems biology
  • Molecular biology
  • Biophysics

Background:

  • Gene expression is fundamental to cellular function.
  • Understanding the efficiency of gene circuits is crucial for synthetic biology.
  • Biological systems balance speed, accuracy (noise), and resource consumption (metabolic cost).

Purpose of the Study:

  • To analyze the trade-offs between information propagation speed, output noise, and metabolic cost in gene expression.
  • To identify optimal design principles for efficient gene circuits.
  • To determine the impact of system parameters like leakiness, Hill coefficient, and threshold on performance.

Main Methods:

  • Mathematical modeling of gene expression dynamics.
  • Analysis of the relationship between system parameters and performance metrics (speed, noise, cost).
  • Identification of optimal parameter values that balance competing objectives.

Main Results:

  • A fundamental trade-off exists between noise and processing speed for a given metabolic cost.
  • Systems with non-vanishing leak expression rates are suboptimal, exhibiting higher noise and/or slower speeds compared to leak-free systems.
  • Optimal values for the Hill coefficient (h) and threshold (K) were identified to minimize noise and metabolic cost at fixed speeds.

Conclusions:

  • Leak-free gene expression systems offer superior performance in terms of speed and noise for a given metabolic cost.
  • Optimizing the Hill coefficient and threshold is critical for efficient gene circuit design.
  • These findings provide insights into the design principles of biological information processing and inform synthetic biology applications.