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

Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

833
Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
833
Next-generation Sequencing03:00

Next-generation Sequencing

100.9K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
100.9K
RNA-seq03:21

RNA-seq

12.4K
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...
12.4K

You might also read

Related Articles

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

Sort by
Same author

Comparison of unbiased metagenomic next generation sequencing to targeted multiplex diagnostic assays for the detection of respiratory viruses.

PloS one·2026
Same author

Beyond Human Papillomavirus (HPV): Detection of EBV and Polyomaviruses in Cervical and Anal Samples.

Journal of medical virology·2026
Same author

Real-world Use of Molecular Point-of-care Testing for Sexually Transmitted Infections (STIs) in the Emergency Department: Why It Matters for Acute Care Management.

Open forum infectious diseases·2026
Same author

Prevalence and co-occurrence of sexually transmitted infections among heterosexual couples in southern Uganda: a population-based study.

Sexually transmitted infections·2025
Same author

Chlamydia and Gonorrhea Infections in Genital and Extragenital Samples Among Men and Women.

Sexually transmitted diseases·2025
Same author

Attitudes towards and use of point-of-care tests for STIs: results from a survey of STI conference attendees in 2023.

Sexual health·2025

Related Experiment Video

Updated: Mar 27, 2026

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria
10:27

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria

Published on: November 10, 2015

12.2K

Nested Machine Learning Facilitates Increased Sequence Content for Large-Scale Automated High Resolution Melt

Stephanie I Fraley1,2, Pornpat Athamanolap3, Billie J Masek2,4

  • 1Bioengineering, The University of California San Diego, La Jolla, California, 92093, USA.

Scientific Reports
|January 19, 2016
PubMed
Summary
This summary is machine-generated.

High Resolution Melt (HRM) analysis combined with a novel nested support vector machine (SVM) approach accurately identifies bacterial species using longer DNA sequences. This method shows promise for clinical diagnostics with further optimization.

More Related Videos

Rapid and Efficient Zebrafish Genotyping Using PCR with High-resolution Melt Analysis
06:30

Rapid and Efficient Zebrafish Genotyping Using PCR with High-resolution Melt Analysis

Published on: February 5, 2014

23.1K
Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.7K

Related Experiment Videos

Last Updated: Mar 27, 2026

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria
10:27

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria

Published on: November 10, 2015

12.2K
Rapid and Efficient Zebrafish Genotyping Using PCR with High-resolution Melt Analysis
06:30

Rapid and Efficient Zebrafish Genotyping Using PCR with High-resolution Melt Analysis

Published on: February 5, 2014

23.1K
Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.7K

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genetics

Background:

  • High Resolution Melt (HRM) is a rapid post-PCR DNA analysis method for differentiating sequence variants in short amplicons.
  • Current HRM applications are limited to analyzing a small number of short DNA sequences.
  • A previously developed one-vs-one support vector machine (OVO SVM) algorithm enhanced HRM for automated identification of multiple short amplicon sequences.

Purpose of the Study:

  • To enhance the discriminatory power of HRM combined with SVM (HRM+SVM) for a single genetic locus.
  • To investigate the utility of longer amplicons containing more sequence information for improved HRM analysis.
  • To develop and validate a novel nested OVO SVM approach for accurate identification of bacterial species.

Main Methods:

  • Utilized universal primers to amplify the hypervariable bacterial 16S rRNA gene, a model system for sequence analysis.
  • Tested longer amplicons to capture more sequence information and generate complex HRM curve shapes.
  • Developed and applied a novel nested OVO SVM approach to analyze the complex HRM data from longer amplicons.

Main Results:

  • Longer amplicons resulted in more complex HRM curve shapes, providing richer data for analysis.
  • The novel nested OVO SVM approach achieved 100% accuracy in identifying 37 clinically relevant bacteria via Leave-One-Out-Cross-Validation.
  • Testing of pure cultures yielded high accuracy, while direct testing from clinical blood bottles showed technical variability and reduced accuracy, indicating a need for further optimization.

Conclusions:

  • Long DNA sequences can be accurately and automatically profiled using HRM with the developed nested SVM approach.
  • The findings suggest the feasibility of HRM+SVM for clinical sample testing, pending further methodological refinement.
  • This enhanced HRM+SVM strategy significantly improves the identification capabilities for bacterial species.