Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

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...
Synthetic Biology02:55

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...
Circadian Rhythms and Gene Regulation02:19

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,...
Constitutive and Regulated Gene Expression01:27

Constitutive and Regulated Gene Expression

Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...
The Central Dogma01:20

The Central Dogma

The central dogma explains the flow of genetic information from DNA nucleotides to the amino acid sequence of proteins.
RNA is the Missing Link Between DNA and Proteins
In the early 1900s, scientists discovered that DNA stores all the information needed for cellular functions and that proteins perform most of these functions. However, the mechanisms of converting genetic information into functional proteins remained unknown for many years. Initially, it was believed that a single gene is...
Operon Model01:23

Operon Model

The operon model represents a fundamental mechanism of gene regulation in prokaryotes, enabling coordinated expression of genes involved in related metabolic or functional pathways. Operons consist of structural genes, a promoter, and an operator, with transcription regulated by repressors, activators, and small effector molecules.Structure and Function of OperonsAn operon is a cluster of structural genes transcribed together under the control of a single promoter. The promoter region...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Growth control as a central regulator for tuning the cellular context.

Journal of biological engineering·2026
Same author

Biocomputation: Moving Beyond Turing with Living Cellular Computers.

Communications of the ACM·2026
Same author

Parameter Evolvability in Gene Expression Models Drives Phenotypic Adaptation.

ALIFE : proceedings of the artificial life conference. International Conference on Artificial Life·2026
Same author

Automated workflow for genotyping individual transposon library variants.

BMC methods·2026
Same author

Dynamics of genetic circuits in Pseudomonas protegens.

Cell systems·2026
Same author

Exploring the computing power of microbes that shapes the environment.

Current opinion in microbiology·2026
Same journal

Ruliological Resilience: Pattern Restoration and Robustness in Wolfram Patterns. A Basis for Regeneration, Not Just in Cone Shells?

Bio Systems·2026
Same journal

The quantum-to-classical transducer: A thermodynamic and quantum mechanical framework for the emergence of bioenergetics.

Bio Systems·2026
Same journal

Forward-backward gene expression binarization for boolean state inference over a known regulatory network.

Bio Systems·2026
Same journal

Partial-label metric ceilings for evaluating gene regulatory networks inferred from single-cell foundation models.

Bio Systems·2026
Same journal

The impedance mismatch theory: A non-equilibrium thermodynamic framework for a shared energetic stress pathway in neurodegeneration.

Bio Systems·2026
Same journal

Immune signal-status misclassification: A theoretical framework for biological status assignment and failed status resolution.

Bio Systems·2026
See all related articles

Related Experiment Video

Updated: May 24, 2026

Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins
10:46

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

Published on: October 18, 2022

Continuous computation in engineered gene circuits.

Angel Goñi-Moreno1, Martyn Amos

  • 1School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, United Kingdom. a.moreno@mmu.ac.uk

Bio Systems
|March 6, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a novel design for genetic circuits using continuous computation to improve reliability. The research demonstrates in vivo implementation of computer architecture concepts like branch prediction for enhanced synthetic biology systems.

More Related Videos

A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression
11:23

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

Published on: October 6, 2019

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells
09:20

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells

Published on: July 6, 2021

Related Experiment Videos

Last Updated: May 24, 2026

Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins
10:46

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

Published on: October 18, 2022

A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression
11:23

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

Published on: October 6, 2019

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells
09:20

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells

Published on: July 6, 2021

Area of Science:

  • Synthetic biology
  • Systems biology
  • Bioengineering

Background:

  • Genetic circuits are fundamental to synthetic biology, but their reliability is often limited by representation and measurement challenges.
  • Current engineered biological systems face issues with signal processing and noise, impacting predictable function.

Purpose of the Study:

  • To address the challenges of representation and measurement in genetic circuits.
  • To propose and validate a novel design scheme for enhancing the reliability of engineered biological systems.
  • To explore the in vivo implementation of computational concepts within genetic circuits.

Main Methods:

  • Developed a design scheme based on the principle of continuous computation.
  • Illustrated the methodology by implementing a branch prediction concept from computer architecture.
  • Utilized a distributed approach for in vivo implementation.
  • Conducted simulation studies to evaluate the proposed method.

Main Results:

  • Simulation results confirmed the in-principle feasibility of the continuous computation design scheme.
  • The implemented branch prediction concept demonstrated potential for improved genetic circuit function.
  • The distributed approach showed promise for robust biological system engineering.

Conclusions:

  • The proposed continuous computation design scheme offers a viable strategy for improving genetic circuit reliability.
  • Implementing computational concepts like branch prediction in vivo is feasible and beneficial for synthetic biology.
  • Further laboratory validation is warranted to confirm simulation findings and advance practical applications.