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

DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

You might also read

Related Articles

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

Sort by

Same author

A decade of progress towards the elimination of hepatitis C: from the National Strategic Plan to Artificial Intelligence.

Gastroenterologia y hepatologia·2026

Same author

Menopause age and hypercholesterolemia comorbidities: a region-wide retrospective cohort study in Andalusia, Spain (2016-2022).

BMJ open·2026

Same author

IMPaCT-Data: A Federated Precision Medicine Infrastructure Associated with Science and Technology in Spain.

Studies in health technology and informatics·2026

Same author

High-Fidelity Synthetic Data Replicates Clinical Prediction Performance in a Million-Patient Diabetes Cohort.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Same author

Cocirculation of endemic and recently introduced West Nile Virus lineage 1 clades in Southern Spain.

One health (Amsterdam, Netherlands)·2026

Same author

Ethical and secure evidence generation from regionwide clinical data through a collaborative environment for advancing predictive care.

Frontiers in public health·2025

Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026

Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026

Same journal

EDEL: Enhancing Dense Retrievers for Curation of Biomedical Knowledge Bases.

Bioinformatics (Oxford, England)·2026

Same journal

Informative Relational Learning for Adverse Reaction Prediction with Enhanced Generalization to Novel Drugs.

Bioinformatics (Oxford, England)·2026

Same journal

An interpretable deep learning framework uncovers features governing CRISPR-Cas9 genome-editing efficiency.

Bioinformatics (Oxford, England)·2026

Same journal

3DICE: Interpretable 3D Cross-Modal Learning for Drug-Target Interaction Prediction and Large-Scale Drug Discovery.

Bioinformatics (Oxford, England)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 10, 2026

Methodology for Accurate Detection of Mitochondrial DNA Methylation

Methodology for Accurate Detection of Mitochondrial DNA Methylation

Published on: May 20, 2018

A parallel and sensitive software tool for methylation analysis on multicore platforms.

Joaquín Tárraga¹, Mariano Pérez², Juan M Orduña²

¹Department of Computational Genomics, Centro de Investigación Príncipe Felipe.

Bioinformatics (Oxford, England)

|June 13, 2015

Summary

This summary is machine-generated.

HPG-Methyl is a new DNA methylation analysis tool that significantly speeds up processing time for bisulfite sequencing reads. It efficiently maps DNA fragments, outperforming existing software, especially for longer reads.

More Related Videos

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain

Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain

Published on: July 12, 2012

Related Experiment Videos

Last Updated: Apr 10, 2026

Methodology for Accurate Detection of Mitochondrial DNA Methylation

Methodology for Accurate Detection of Mitochondrial DNA Methylation

Published on: May 20, 2018

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Enhanced Reduced Representation Bisulfite Sequencing for Assessment of DNA Methylation at Base Pair Resolution

Published on: February 24, 2015

Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain

Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain

Published on: July 12, 2012

Area of Science:

Genomics
Bioinformatics

Background:

DNA methylation analysis is computationally intensive, posing a bottleneck in genomic studies.
Current software struggles to scale with increasing dataset sizes and read lengths.
Advancements in Next-Generation Sequencing necessitate more efficient and scalable analysis tools.

Purpose of the Study:

To develop a novel software tool for efficient and scalable DNA methylation analysis.
To address the limitations of existing methylation analysis software in terms of speed and scalability.

Main Methods:

HPG-Methyl utilizes the Burrows-Wheeler Transform for rapid mapping of DNA fragments.
The Smith-Waterman algorithm is selectively applied to ambiguous and shorter reads for accuracy.
The software is implemented as C libraries and functions.

Main Results:

HPG-Methyl demonstrates significantly improved execution time and sensitivity compared to state-of-the-art tools like Bismark, BS-Seeker, and BSMAP.
The performance gains are particularly notable for long bisulfite reads.
Experimental results confirm the efficiency and scalability of HPG-Methyl on multicore processors.

Conclusions:

HPG-Methyl offers a substantial improvement in DNA methylation analysis efficiency.
The tool is well-suited for handling the increasing read lengths from modern sequencing platforms.
HPG-Methyl represents a scalable solution for genomic studies involving DNA methylation analysis.