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...

You might also read

Related Articles

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

Sort by

Same author

Prioritizing peptides for targeted mass spectrometry experiments using deep learning.

bioRxiv : the preprint server for biology·2026

Same author

Embryo-scale Visual Cell Sorting reveals a conserved transcriptomic signature of nucleolar size linked to proteostasis.

bioRxiv : the preprint server for biology·2026

Same author

Detection and classification of lymphoma from cell-free methylome data.

NPJ precision oncology·2026

Same author

A divergent Plasmodium NEK4 acts as a key regulator driving the early events of meiosis.

Nature communications·2026

Same author

Segzoo: a turnkey system that summarizes genome annotations.

Bioinformatics (Oxford, England)·2026

Same author

Host-cell dependent epigenetic profiles associated with survival outcomes in T. gondii infection.

Epigenetics & chromatin·2026

Search research articles

Related Experiment Video

Updated: May 28, 2026

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

Published on: October 5, 2018

Exploratory analysis of genomic segmentations with Segtools.

Orion J Buske¹, Michael M Hoffman, Nadia Ponts

¹Department of Genome Sciences, University of Washington, PO Box 355065, Seattle, WA 98195-5065, USA.

BMC Bioinformatics

|October 28, 2011

Summary

Researchers can now easily interpret large-scale genomic data with Segtools. This software automates the exploration of genomic segmentations, simplifying functional genomics analysis.

More Related Videos

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Related Experiment Videos

Last Updated: May 28, 2026

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

Published on: October 5, 2018

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Genome-wide experiments and annotations are increasingly common.
Interpreting large-scale genomic data requires specialized tools.
Functional genomics experiments often involve partitioning the genome into labeled segments.

Purpose of the Study:

To present a software toolkit for exploring genomic segmentations.
To simplify and automate the analysis of functional genomics data.

Main Methods:

Development of the Segtools software toolkit.
Utilizing a series of interacting tools for data summarization.
Pipelining tools for consolidated HTML page output.

Main Results:

Segtools simplifies and automates the exploration of genomic segmentations.
Demonstrated utility in interpreting human histone modification data.
Applied to Plasmodium falciparum local chromatin structure data analysis.

Conclusions:

Segtools offers a powerful and convenient method for interpreting genomic segmentations.
Facilitates the understanding of complex functional genomics datasets.