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HSeeker: an algorithm for systematic H-DNA sequence identification
Kimonas Provatas1, Guliang Wang1, Nikol Chantzi1
1Division of Pharmacology and Toxicology, College of Pharmacy, The University of Texas at Austin, Dell Pediatric Research Institute, Austin, TX, USA.
Biorxiv : the Preprint Server for Biology
|July 29, 2026
Summary
HSeeker is a new computational tool that identifies and scores DNA triplex (H-DNA) forming sequences. It offers a more comprehensive analysis of H-DNA stability and distribution in genomic data.
Area of Science:
- Genomics
- Computational Biology
- Molecular Biology
Background:
- H-DNA is a naturally occurring DNA triplex structure crucial for gene regulation and disease.
- Existing detection tools miss key H-DNA sequence features and stability aspects.
Purpose of the Study:
- To develop a comprehensive computational tool for identifying and scoring H-DNA forming sequences.
- To address limitations in current H-DNA detection methods.
Main Methods:
- HSeeker employs a three-part algorithm: center-outward search, greedy overlap removal, and thermodynamic stability scoring.
- The tool allows configurable parameters for mismatches and composition thresholds.
- Stability scoring incorporates Hoogsteen bonds, stacking interactions, and mismatch penalties.
Main Results:
- HSeeker identifies and scores potential H-DNA sequences with detailed genomic coordinates and stability metrics.
- The tool optimizes motif boundaries and provides a user-friendly interface (Python package and web app).
- It enables high-throughput, configurable analysis and export of predicted H-DNA motifs.
Conclusions:
- HSeeker offers an accessible and reproducible framework for studying H-DNA distribution and stability.
- This tool enhances the investigation of H-DNA's role in gene regulation, genome instability, and human disease.
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