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Related Concept Videos

Genome Annotation and Assembly03:36

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.
The Replisome03:01

The Replisome

DNA replication is carried out by a large complex of proteins that act in a coordinated matter to achieve high-fidelity DNA replication. Together this complex is known as the DNA replication machinery or the replisome.
The synthesis of the leading and lagging strands is a highly coordinated process. To explain this, the “Trombone model” was proposed by Bruce Alberts in 1980. The DNA loop formation starts when a primer is synthesized on the parent lagging strand. The loop grows with the...
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Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...

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Related Experiment Video

Updated: Jun 14, 2026

Automated Robotic Liquid Handling Assembly of Modular DNA Devices
11:22

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

Algorithms for automated DNA assembly.

Douglas Densmore1, Timothy H-C Hsiau, Joshua T Kittleson

  • 1Department of Fuel Synthesis, Joint BioEnergy Institute, 5885 Hollis St., Fourth Floor, Emeryville CA 94608, USA. dmdensmore@lbl.gov

Nucleic Acids Research
|March 26, 2010
PubMed
Summary
This summary is machine-generated.

This study presents algorithms for optimizing DNA assembly, reducing costs and errors in biological engineering. These computational tools efficiently design genetic constructs for novel functions.

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Last Updated: Jun 14, 2026

Automated Robotic Liquid Handling Assembly of Modular DNA Devices
11:22

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

Self-assembly of Complex Two-dimensional Shapes from Single-stranded DNA Tiles
10:23

Self-assembly of Complex Two-dimensional Shapes from Single-stranded DNA Tiles

Published on: May 8, 2015

Area of Science:

  • Synthetic Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Assembling multiple DNA sequences for novel biological functions is complex, costly, and prone to errors.
  • Manual design of DNA fabrication schemes is often suboptimal and time-consuming.
  • There is a need for modular, robust, and formal approaches to explore vast design spaces in biological engineering.

Purpose of the Study:

  • To develop and present algorithms that optimize the simultaneous assembly of a collection of related DNA sequences.
  • To automate the design of DNA fabrication schemes, minimizing human error, redundant operations, time, and cost.
  • To provide efficient computational solutions for exploring large design spaces in genetic construct generation.

Main Methods:

  • Development of computational algorithms for optimizing DNA fabrication schemes.
  • Comparison of developed algorithms against exhaustive search on a small synthetic dataset.
  • Evaluation of algorithms using random search approaches on two real-world datasets.

Main Results:

  • Algorithms quickly find optimal solutions for simultaneous DNA sequence assembly on small datasets.
  • Algorithms efficiently identify lower-cost solutions for large, real-world datasets.
  • Automated design significantly reduces time and cost compared to manual methods.

Conclusions:

  • Automated, algorithm-driven design of DNA fabrication schemes is superior to manual approaches.
  • The developed algorithms offer a robust and efficient method for complex genetic construct assembly.
  • This work streamlines biological engineering experiments by minimizing errors and optimizing resource utilization.