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

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.1K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
6.1K
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

81
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...
81
Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

12.6K
The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
12.6K
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

11.4K
In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
11.4K
RNA-seq03:21

RNA-seq

10.3K
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...
10.3K

You might also read

Related Articles

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

Sort by
Same author

Effect of an intensive antiplaque regimen on microbiome outcomes after nonsurgical periodontal therapy.

Journal of periodontology·2025
Same author

Prostate Cancer Progression Modeling Provides Insight into Dynamic Molecular Changes Associated with Progressive Disease States.

Cancer research communications·2024
Same author

Identifying Significantly Perturbed Subnetworks in Cancer Using Multiple Protein-Protein Interaction Networks.

Cancers·2023
Same author

An efficient and effective method to identify significantly perturbed subnetworks in cancer.

Nature computational science·2023
Same author

Neutrophil extracellular traps and extracellular histones potentiate IL-17 inflammation in periodontitis.

The Journal of experimental medicine·2023
Same author

KREH1 RNA helicase activity promotes utilization of initiator gRNAs across multiple mRNAs in trypanosome RNA editing.

Nucleic acids research·2023

Related Experiment Video

Updated: Aug 21, 2025

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.4K

Alignment-free comparison of metagenomics sequences via approximate string matching.

Jian Chen1, Le Yang2, Lu Li3

  • 1Department of Computer Science and Engineering, University at Buffalo, Buffalo, NY 14260, USA.

Bioinformatics Advances
|November 17, 2022
PubMed
Summary

A new method, AsMac, improves sequence similarity quantification in metagenomics. It uses a novel neural network to overcome limitations of existing alignment-free approaches for varying sequence lengths and insertions/deletions.

More Related Videos

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
11:23

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Published on: December 22, 2014

37.3K
Metagenomic Analysis of Silage
08:43

Metagenomic Analysis of Silage

Published on: January 13, 2017

18.5K

Related Experiment Videos

Last Updated: Aug 21, 2025

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.4K
Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
11:23

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

Published on: December 22, 2014

37.3K
Metagenomic Analysis of Silage
08:43

Metagenomic Analysis of Silage

Published on: January 13, 2017

18.5K

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • Accurate pairwise sequence similarity quantification is crucial for metagenomics.
  • Alignment-free methods offer computational efficiency for large-scale sequence analysis.
  • Existing neural network methods struggle with variable sequence lengths and indels.

Purpose of the Study:

  • To develop a novel alignment-free method, AsMac, for robust sequence similarity quantification.
  • To address limitations of current methods regarding sequence length variation and insertions/deletions.
  • To provide an efficient and effective tool for metagenomic data analysis.

Main Methods:

  • Proposed a novel neural network architecture for approximate string matching.
  • Developed an efficient gradient computation algorithm for neural network training.
  • Utilized real-world data for large-scale benchmarking.

Main Results:

  • The AsMac method demonstrates effectiveness in quantifying pairwise sequence similarities.
  • The approach successfully handles sequences of varying lengths.
  • The method shows improved performance in the presence of insertions and deletions.

Conclusions:

  • AsMac offers a significant advancement in alignment-free sequence analysis for metagenomics.
  • The developed method is computationally efficient and robust.
  • Open-source software and trained models are available for broader application.