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

5.7K
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...
5.7K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

17.0K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
17.0K

You might also read

Related Articles

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

Sort by
Same author

Analysis of isoform complexity in pan-transcriptome graphs with atroplex.

bioRxiv : the preprint server for biology·2026
Same author

An EGFR co-amplified lncRNA HELDR promotes glioblastoma malignancy through KAT7-driven gene programs.

Nature cell biology·2026
Same author

Tumor-specific lncRNA IGF1R-AS1 trans-regulates chromatin interactions associated with oncogenic MYC signaling.

Nature communications·2026
Same author

Genomic language model mitigates chimera artifacts in nanopore direct RNA sequencing.

Nature communications·2026
Same author

The RNA N<sup>6</sup>-methyladenosine methylome coordinates long non-coding RNAs to mediate cancer drug resistance by activating PI3K signaling.

Cell death & disease·2025
Same author

A comprehensive benchmark of tools for efficient genomic interval querying.

Briefings in bioinformatics·2025

Related Experiment Video

Updated: May 23, 2025

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
04:58

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

Published on: December 13, 2024

2.0K

A Comprehensive Benchmark of Tools for Efficient Genomic Interval Querying.

Richard A Schäfer1, Rendong Yang2

  • 1Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611.

Biorxiv : the Preprint Server for Biology
|March 10, 2025
PubMed
Summary

We evaluated genomic interval query tools for bioinformatics, finding segmeter offers a comprehensive benchmark. Our analysis guides researchers in selecting optimal tools for genomic data analysis based on performance and memory needs.

Keywords:
datagenomic featuresintervalquery

More Related Videos

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

8.8K
Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization
16:37

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

Published on: August 5, 2008

12.7K

Related Experiment Videos

Last Updated: May 23, 2025

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
04:58

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance

Published on: December 13, 2024

2.0K
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

8.8K
Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization
16:37

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

Published on: August 5, 2008

12.7K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomic Data Analysis

Background:

  • Genomic interval querying is crucial for analyzing large biological datasets.
  • Existing tools lack comprehensive performance and utility comparisons.
  • Efficient data retrieval is essential for advancing genomic research.

Purpose of the Study:

  • To systematically evaluate and compare the performance of genomic interval query tools.
  • To introduce the segmeter benchmarking framework for assessing query efficiency.
  • To provide guidance for selecting appropriate tools based on specific research needs.

Main Methods:

  • Utilized simulated genomic datasets of varying sizes for benchmarking.
  • Employed the segmeter framework to assess runtime, memory usage, and query precision.
  • Compared multiple genomic interval query tools and data structures.

Main Results:

  • Identified performance variations and memory efficiency differences among tools.
  • Demonstrated segmeter's capability to evaluate both basic and complex interval queries.
  • Highlighted the strengths and limitations of different genomic interval querying approaches.

Conclusions:

  • The study provides critical insights into the practical utility of genomic interval query tools.
  • Segmeter facilitates reproducible benchmarking and aids tool selection for genomic data analysis.
  • Open availability of the framework and data promotes further research and development.