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

Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.

Maxam-Gilbert Sequencing

Maxam-Gilbert Sequencing

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...

Sanger Sequencing

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...

You might also read

Related Articles

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

Sort by

Same author

Germline hypomethylation shapes dynamic CpG reservoirs in ape genomes.

bioRxiv : the preprint server for biology·2026

Same author

The clinical features, pathological assessment, and prognostic analysis of autoimmune hepatitis in Chinese persons living with HIV.

BMC infectious diseases·2026

Same author

Endoplasmic reticulum-resident α-glucosidase II drives non-small cell lung cancer progression via regulation of secretory glycoproteins.

JCI insight·2026

Same author

Uncertainty-aware synthetic lethality prediction with pretrained foundation models.

bioRxiv : the preprint server for biology·2026

Same author

High-throughput simultaneous quantification of glycopeptides and phosphopeptides enabled by 12-plex DiLeu isobaric tags and dual-functional Titanium(IV)-IMAC material.

Analytica chimica acta·2026

Same author

QSOX1: A Mysterious Golgi-Localized Disulfide Bond Catalyst and an Emerging Cancer Regulator.

Cancers·2026

Search research articles

Related Experiment Video

Updated: Jun 15, 2026

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

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

Published on: December 13, 2024

DNALONGBENCH: a benchmark suite for long-range DNA prediction tasks.

Wenduo Cheng¹, Zhenqiao Song², Yang Zhang¹

¹Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.

Nature Communications

|November 18, 2025

Summary

We introduce DNALONGBENCH, a new benchmark dataset for evaluating genomics tasks involving long-range DNA dependencies up to 1 million base pairs. This resource aids in developing advanced deep learning models for genome structure and function analysis.

More Related Videos

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Related Experiment Videos

Last Updated: Jun 15, 2026

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

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

Published on: December 13, 2024

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Area of Science:

Genomics
Computational Biology
Bioinformatics

Background:

Modeling long-range DNA dependencies is essential for understanding genome structure and function.
Current methods struggle to capture dependencies spanning millions of base pairs, particularly in 3D chromatin folding prediction.
A lack of comprehensive benchmarks hinders the evaluation of models addressing these long-range interactions.

Purpose of the Study:

To introduce DNALONGBENCH, a novel benchmark dataset designed to evaluate genomics tasks reliant on long-range DNA dependencies.
To provide a standardized resource for comparing and assessing deep learning models for genomics.
To facilitate advancements in understanding genome structure and function by addressing the challenge of long-range dependencies.

Main Methods:

DNALONGBENCH encompasses five key genomics tasks: enhancer-target gene interaction, expression quantitative trait loci (eQTLs), 3D genome organization, regulatory sequence activity, and transcription initiation signals.
The benchmark covers DNA dependencies up to 1 million base pairs.
Evaluation involved five distinct models: a task-specific expert model, a convolutional neural network (CNN), and three fine-tuned DNA foundation models (HyenaDNA, Caduceus-Ph, Caduceus-PS).

Main Results:

The study establishes DNALONGBENCH as a comprehensive resource for evaluating long-range DNA dependency modeling.
Performance comparisons across different model types were conducted on the benchmark tasks.
The benchmark facilitates rigorous evaluation of emerging deep learning models in genomics.

Conclusions:

DNALONGBENCH addresses the critical need for a standardized benchmark in genomics research focused on long-range DNA dependencies.
This dataset will accelerate the development and validation of sophisticated deep learning models for complex genomic analyses.
The resource is expected to drive progress in understanding genome organization, gene regulation, and disease association studies.