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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

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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....
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Updated: Jul 6, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
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Adapting Nanopore Sequencing Basecalling Models for Modification Detection via Incremental Learning and Anomaly

Ziyuan Wang1,2, Yinshan Fang3,2, Ziyang Liu1,4

  • 1Department of Pharmacy Practice and Science, University of Arizona, Tucson, Arizona, USA.

Biorxiv : the Preprint Server for Biology
|January 8, 2024
PubMed
Summary

This study introduces a machine learning pipeline for detecting nucleotide modifications using nanopore sequencing. The method achieves single-molecule, single-nucleotide resolution for accurate basecalling and modification status determination.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Nanopore sequencing offers real-time data acquisition but requires accurate basecalling.
  • Detecting nucleotide modifications is crucial for understanding gene regulation and disease.
  • Existing methods for modification detection can be limited in resolution or scope.

Conclusions:

  • The developed IL-AD workflow provides a robust method for single-molecule, single-nucleotide modification detection.
  • This approach enhances the utility of nanopore sequencing for epigenomic studies.
  • The pipeline is publicly available for broader research applications.