A Unified Statistical Procedure to Analyse Irreversible Thermal Curves

[2209.03957] A Unified Statistical Procedure to Analyse Irreversible Thermal Curves Skip to main content Search Submit Donate Log in Physics > Chemical Physics arXiv:2209.03957 (physics) [Submitted on 2 Sep 2022 ( v1 ), last revised 27 Aug 2026 (this version, v2)] Title: A Unified Statistical Procedure to Analyse Irreversible Thermal Curves Authors: Sanjay Chaudhuri , Dang Trung Kien , Gopinatha Suresh Kumar , Souvik Maiti , Daisuke Miyoshi , Jhimli Bhattacharyya View PDF HTML (experimental) Abstract: DNA hybridisation experiments are crucial for studying the thermodynamic and kinetic profiles of various systems in nucleic acid chemistry. The phenomenon of hysteresis is commonly observed in many such UV thermal experiments involving unmodified or modified nucleic acids. In the presence of hysteresis, the thermal curves are irreversible and demand a significant effort to produce the reaction-specific kinetic and thermodynamic parameters. In this article, we describe a unified statistical procedure to analyse such thermal curves. More specifically, the proposed method allows one to handle the thermal curves for the formation of duplexes, triplexes, and various quadruplexes in exactly the same way. The proposed method uses a local polynomial regression to find the smoothed thermal curves and calculate their slopes. This method is more flexible and easier to implement than the least squares polynomial smoothing, which is currently almost universally used for such purposes. Full analyses of the curves, including computation of kinetic and thermodynamic parameters, can be done using freely available statistical software. The proposed procedure has been implemented in a web-based free software called anhysnuc, which can be found at this https URL . Finally, we illustrate our method by analysing irreversible curves encountered in the formation of a G-quadruplex and an LNA-modified parallel duplex. Subjects: Chemical Physics (physics.chem-ph) ; Applications (stat.AP); Computation (stat.CO); Methodology (stat.ME) Cite as: arXiv:2209.03957 [physics.chem-ph] (or arXiv:2209.03957v2 [physics.chem-ph] for this version) https://doi.org/10.48550/arXiv.2209.03957 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Sanjay Chaudhuri [ view email ] [v1] Fri, 2 Sep 2022 21:19:39 UTC (41 KB) [v2] Thu, 27 Aug 2026 00:05:12 UTC (1,055 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: physics.chem-ph < prev | next > new | recent | 2022-09 Change to browse by: physics stat stat.AP stat.CO stat.ME References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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