Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

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...

Gene Evolution - Fast or Slow?

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...

Phylogenetic Trees

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.

Karyotyping

Karyotyping

You might also read

Related Articles

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

Sort by

Same author

Movi Color: fast and accurate taxonomic classification with the move structure.

ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine·2026

Same author

Faster run-length compressed suffix arrays.

Oasics : openaccess series in informatics·2026

Same author

Minimizing reference bias with an imputed personalized reference.

Genome research·2026

Same author

RLBWT-Based LCP Computation in Compressed Space for Terabase-Scale Pangenome Analysis.

bioRxiv : the preprint server for biology·2026

Same author

KeBaB: <i>k</i>-mer based breaking for finding long MEMs.

International Symposium on String Processing and Information Retrieval : SPIRE ... : proceedings. SPIRE (Symposium)·2025

Same author

Prefix-free parsing for merging big BWTs.

International Symposium on String Processing and Information Retrieval : SPIRE ... : proceedings. SPIRE (Symposium)·2025

Same journal

Layered social competition coordinates reproductive hierarchy formation in ants.

bioRxiv : the preprint server for biology·2026

Same journal

Combination epigenetic-targeted therapy increases the immunogenicity of poorly immunogenic sarcomas.

bioRxiv : the preprint server for biology·2026

Same journal

Loss of LanC-like proteins delays post-injury regeneration of aging skeletal muscles.

bioRxiv : the preprint server for biology·2026

Same journal

Integrative Transfer Network: Deep Transfer Learning Across Populations and Prediction Targets.

bioRxiv : the preprint server for biology·2026

Same journal

Confidence-supported label-free metabolic imaging with FPhaS phase autofluorescence microscopy.

bioRxiv : the preprint server for biology·2026

Same journal

Sequence-encoded autoinhibition couples mRNA decapping activity to phase separation.

bioRxiv : the preprint server for biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 7, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Improved pangenomic classification accuracy with chain statistics.

Nathaniel K Brown¹, Vikram S Shivakumar¹, Ben Langmead¹

¹Department of Computer Science, Johns Hopkins University, Baltimore MD 21218.

Biorxiv : the Preprint Server for Biology

|November 18, 2024

Summary

This summary is machine-generated.

This study introduces a new compressed full-text index for efficient sequence classification. It captures both fine-grained and coarse-grained co-linearity, improving accuracy over previous methods.

Keywords:

Pangenomics sequence classification text indexing

More Related Videos

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

qPCRTag Analysis - A High Throughput, Real Time PCR Assay for Sc2.0 Genotyping

qPCRTag Analysis - A High Throughput, Real Time PCR Assay for Sc2.0 Genotyping

Published on: May 25, 2015

Related Experiment Videos

Last Updated: Jun 7, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

qPCRTag Analysis - A High Throughput, Real Time PCR Assay for Sc2.0 Genotyping

qPCRTag Analysis - A High Throughput, Real Time PCR Assay for Sc2.0 Genotyping

Published on: May 25, 2015

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Compressed full-text indexes facilitate efficient sequence classification.
Previous methods using matching statistics or pseudo-matching lengths captured fine-grained co-linearity but missed coarse-grained information.

Purpose of the Study:

To develop a novel compressed-index approach for sequence classification.
To incorporate coarse-grained co-linearity (chain) statistics without superlinear time complexity.

Main Methods:

Computed multi-maximal unique matches (multi-MUMs) and identified Burrows-Wheeler Transform (BWT) sub-runs.
Selected and marked BWT sub-runs corresponding to multi-MUMs using a tunneling approach.
Constructed a compressed index enabling simultaneous computation of fine-grained and coarse-grained statistics.

Main Results:

Achieved an index with space complexity related to the number of sequences and BWT runs.
Enabled linear-time computation of both fine-grained matching and coarse-grained chain statistics.
Demonstrated substantial improvement in classification accuracy compared to prior compressed-indexing methods.

Conclusions:

The novel approach significantly enhances sequence classification accuracy.
The method matches the accuracy of less efficient alignment-based techniques.
This work advances compressed indexing for large-scale genomic analysis.