ArticleBioinformatics (Oxford, England)2023
Examining DNA breathing with pyDNA-EPBD.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A Smart Single-Loop-Mediated Isothermal Amplification Facilitates Flexible SNP Probe Design for On-Site Rapid Differentiation of SARS-CoV-2 Omicron Variants.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Melting Profile of DNA in Crowded Solution: Model-Based Study.International journal of molecular sciences · 2025Article
- Contribution of DNA breathing to physical interactions with transcription factors.bioRxiv : the preprint server for biology · 2025Article
- Efficient High-Throughput DNA Breathing Features Generation Using Jax-EPBD.bioRxiv : the preprint server for biology · 2024Article
- DNA breathing integration with deep learning foundational model advances genome-wide binding prediction of human transcription factors.Nucleic acids research · 2024Article
- Advancing Transcription Factor Binding Site Prediction Using DNA Breathing Dynamics and Sequence Transformers via Cross Attention.bioRxiv : the preprint server for biology · 2024Article
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7 authors.
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Abstract
motivationThe two strands of the DNA double helix locally and spontaneously separate and recombine in living cells due to the inherent thermal DNA motion. This dynamics results in transient openings in the double helix and is referred to as "DNA breathing" or "DNA bubbles." The propensity to form local transient openings is important in a wide range of biological processes, such as transcription, replication, and transcription factors binding. However, the modeling and computer simulation of these phenomena, have remained a challenge due to the complex interplay of numerous factors, such as, temperature, salt content, DNA sequence, hydrogen bonding, base stacking, and others.
resultsWe present pyDNA-EPBD, a parallel software implementation of the Extended Peyrard-Bishop-Dauxois (EPBD) nonlinear DNA model that allows us to describe some features of DNA dynamics in detail. The pyDNA-EPBD generates genomic scale profiles of average base-pair openings, base flipping probability, DNA bubble probability, and calculations of the characteristically dynamic length indicating the number of base pairs statistically significantly affected by a single point mutation using the Markov Chain Monte Carlo algorithm. AVAILABILITY AND IMPLEMENTATION: pyDNA-EPBD is supported across most operating systems and is freely available at https://github.com/lanl/pyDNA_EPBD. Extensive documentation can be found at https://lanl.github.io/pyDNA_EPBD/.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.