Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Synthetic Biology

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...

DNA Packaging

DNA Packaging

Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

DNA as a Genetic Template

DNA as a Genetic Template

You might also read

Related Articles

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

Sort by

Same author

APEX: Automated Protein EXpression in <i>Escherichia coli</i>.

ACS synthetic biology·2025

Same author

Construction and iterative redesign of synXVI a 903 kb synthetic Saccharomyces cerevisiae chromosome.

Nature communications·2025

Same author

Protein engineering using variational free energy approximation.

Nature communications·2024

Same author

Dirichlet latent modelling enables effective learning and sampling of the functional protein design space.

Nature communications·2024

Same author

Beyond the marrow: insights from comprehensive next-generation sequencing of extramedullary multiple myeloma tumors.

Leukemia·2024

Same author

Biofoundry-Scale DNA Assembly Validation Using Cost-Effective High-Throughput Long-Read Sequencing.

ACS synthetic biology·2024

Same journal

A CURE for synthetic regulation of gene expression: rapid screening of guide RNA efficacy as a framework for enabling undergraduate research in plant synthetic biology.

Synthetic biology (Oxford, England)·2026

Same journal

Chemically synthesized high-fidelity oligos ≤ 600 nt as building blocks to accelerate complex gene construction in synthetic biology.

Synthetic biology (Oxford, England)·2026

Same journal

Off-target detection of CRISPR-Cas9 nuclease <i>in vitro</i> with CROFT-Seq.

Synthetic biology (Oxford, England)·2026

Same journal

Going beyond size: exploring the metabolic burden in <i>Pseudomonas putida</i> during heterologous protein production.

Synthetic biology (Oxford, England)·2026

Same journal

A protein-fragment complementation assay to quantify synthetic protein scaffold efficiency.

Synthetic biology (Oxford, England)·2026

Same journal

EASY-C: Extraction and Analysis of Small Yeast Chromosomes-A rapid and universal platform for recovering artificial mini-chromosomes from synthetic Sc2.0 yeast and large plasmids from <i>Saccharomyces cerevisiae</i> and nonconventional yeast species.

Synthetic biology (Oxford, England)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Oct 16, 2025

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

Design and assembly of DNA molecules using multi-objective optimization.

Angelo Gaeta¹, Valentin Zulkower², Giovanni Stracquadanio¹

¹School of Biological Sciences, The University of Edinburgh, Edinburgh EH9 3BF, UK.

Synthetic Biology (Oxford, England)

|October 22, 2021

Summary

This summary is machine-generated.

This study introduces a new algorithm to optimize DNA engineering by balancing design needs with manufacturing limits. The open-source tool improves synthetic biology yields and enables rational DNA design from genes to genomes.

Keywords:

biodesign combinatorial assembly computer-aided design multi-objective optimization optimization

More Related Videos

Designing a Bio-responsive Robot from DNA Origami

Designing a Bio-responsive Robot from DNA Origami

Published on: July 8, 2013

Design and Synthesis of a Reconfigurable DNA Accordion Rack

Design and Synthesis of a Reconfigurable DNA Accordion Rack

Published on: August 15, 2018

Related Experiment Videos

Last Updated: Oct 16, 2025

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

Designing a Bio-responsive Robot from DNA Origami

Designing a Bio-responsive Robot from DNA Origami

Published on: July 8, 2013

Design and Synthesis of a Reconfigurable DNA Accordion Rack

Design and Synthesis of a Reconfigurable DNA Accordion Rack

Published on: August 15, 2018

Area of Science:

Synthetic Biology
Bioengineering
Computational Biology

Background:

Synthetic biology workflows are often inefficient due to a lack of manufacturing constraint integration in the design phase.
This limitation reduces the overall yield and scalability of engineering biological systems.

Purpose of the Study:

To address the challenge of integrating manufacturing constraints into the DNA engineering design process.
To develop a method that optimizes synthetic biology workflows by finding a balance between design requirements and production limitations.

Main Methods:

Developed a novel open-source algorithm named Multi-Objective Optimisation algorithm for DNA Design and Assembly (MODDA).
The algorithm treats DNA engineering as a multi-objective optimization problem.
MODDA is available as a Python/Anaconda package and a Docker image for accessibility.

Main Results:

Experimental validation demonstrated that the algorithm produces near-optimal DNA constructs.
The method exhibits linear scalability with increasing design complexity.
Successfully paved the way for rational engineering of DNA molecules.

Conclusions:

The developed algorithm effectively integrates manufacturing constraints into DNA design.
MODDA enhances the efficiency and yield of synthetic biology applications.
Enables rational and scalable engineering of DNA from genes to genomes.