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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.
Next-generation Sequencing03:00

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RNA-seq03:21

RNA-seq

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RACE - Rapid Amplification of cDNA Ends02:35

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Related Experiment Video

Updated: Jun 22, 2026

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
12:08

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

A fast hybrid short read fragment assembly algorithm.

Bertil Schmidt1, Ranjan Sinha, Bryan Beresford-Smith

  • 1School of Computer Engineering, Nanyang Technological University, Singapore. asbschmidt@ntu.edu.sg

Bioinformatics (Oxford, England)
|June 19, 2009
PubMed
Summary
This summary is machine-generated.

New DNA sequencing tools are needed to assemble massive short reads. Taipan, a hybrid assembly algorithm, offers high-quality DNA sequence assembly using fewer computing resources than existing graph-based methods.

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Novel Sequence Discovery by Subtractive Genomics

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Related Experiment Videos

Last Updated: Jun 22, 2026

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
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Published on: August 20, 2021

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14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Second-generation sequencing technologies produce numerous short DNA reads, necessitating efficient assembly algorithms.
  • Current short-read assemblers are primarily greedy extension-based or graph-based.
  • Graph-based assemblers offer superior quality but demand substantial computational resources.

Purpose of the Study:

  • To introduce Taipan, a novel hybrid DNA sequence assembly algorithm.
  • To address the computational challenges of assembling massive short reads from next-generation sequencing.
  • To evaluate Taipan's performance against existing assembly tools.

Main Methods:

  • Taipan employs a hybrid approach, combining greedy extensions for contig construction with partial read graph analysis.
  • The algorithm iteratively builds contigs while referencing the read graph for informed assembly decisions.
  • Performance was benchmarked against established tools like Edena and Velvet.

Main Results:

  • Taipan achieves assembly quality comparable to leading graph-based methods.
  • The algorithm demonstrates efficiency, utilizing moderate computing resources.
  • Successful assembly of massive short-read datasets is feasible with Taipan.

Conclusions:

  • Taipan presents an effective hybrid strategy for short-read assembly.
  • The algorithm balances assembly quality with computational efficiency.
  • Taipan offers a viable solution for large-scale genomic data analysis.