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

RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific primer.
Since the...

You might also read

Related Articles

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

Sort by
Same author

Sequence to structure insights into Lassa virus population-level biophysical properties and glycoprotein structure catalogue.

Npj viruses·2026
Same author

Lassa virus live tracking and lineage assignment: how nextstrain can enhance surveillance and public health in Africa and beyond.

Emerging microbes & infections·2026
Same author

DREAM-Stellar: parallel and space efficient exact local alignment.

BMC bioinformatics·2026
Same author

Engineering rank queries on bit vectors and strings.

Algorithms for molecular biology : AMB·2025
Same author

The AIR·MS data platform for artificial intelligence in healthcare.

JAMIA open·2025
Same author

ganon2: up-to-date and scalable metagenomics analysis.

NAR genomics and bioinformatics·2025

Related Experiment Video

Updated: May 14, 2026

Targeted DNA Methylation Analysis by Next-generation Sequencing
08:38

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Fast and accurate read mapping with approximate seeds and multiple backtracking.

Enrico Siragusa1, David Weese, Knut Reinert

  • 1Department of Mathematics and Computer Science, Freie Universität Berlin, Takustr. 9, 14195 Berlin, Germany. enrico.siragusa@fu-berlin.de

Nucleic Acids Research
|January 30, 2013
PubMed
Summary

Masai is a novel DNA sequence read mapper that significantly improves speed and accuracy. Its innovative methods make approximate searching of genomic data faster and more efficient.

More Related Videos

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
09:14

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

Introductory Analysis and Validation of CUT&RUN Sequencing Data
04:58

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Related Experiment Videos

Last Updated: May 14, 2026

Targeted DNA Methylation Analysis by Next-generation Sequencing
08:38

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
09:14

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

Introductory Analysis and Validation of CUT&RUN Sequencing Data
04:58

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Accurate and efficient read mapping is crucial for analyzing next-generation sequencing (NGS) data.
  • Existing read mappers face challenges in balancing speed and accuracy, especially with large and repetitive genomic datasets.

Purpose of the Study:

  • To introduce Masai, a state-of-the-art DNA sequence read mapper.
  • To present novel algorithmic approaches that enhance the speed and accuracy of read mapping.

Main Methods:

  • Development of Masai, a C++ read mapper utilizing the SeqAn library.
  • Implementation of filtration with approximate seeds to improve specificity while maintaining sensitivity.
  • Introduction of a multiple backtracking method to efficiently search large seed sets by leveraging data repetitiveness.

Main Results:

  • Masai demonstrates an order of magnitude speed improvement over RazerS 3 and mrFAST.
  • Masai is 2-4 times faster and more accurate than established mappers like Bowtie 2 and BWA.
  • The combined novel methods significantly accelerate approximate searching on genomic datasets.

Conclusions:

  • Masai represents a significant advancement in read mapping technology.
  • The tool offers superior performance in terms of speed and accuracy for genomic data analysis.
  • Masai is freely available with source code and binaries for major operating systems.