Graph Convolutional Network for predicting secondary structure of RNA

Graph Convolutional Network for predicting secondary structure of RNA | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Graph Convolutional Network for predicting secondary structure of RNA Dmitry Korkin, Aukkawut ammartayakun, Palawat Busaranuvong, Roya Khosravi-Far This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3798842/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The prediction of RNA secondary structures is essential for understanding its underlying principles and applications in diverse fields, including molecular diagnostics and RNA-based therapeutic strategies. However, the complexity of the search space presents a challenge. This work proposes a Graph Convolutional Network (GCNfold) for predicting the RNA secondary structure. GCNfold considers an RNA sequence as graph-structured data and predicts posterior base-pairing probabilities given the prior base-pairing probabilities, calculated using McCaskill’s partition function. The performance of GCNfold surpasses that of the state-of-the-art folding algorithms, as we have incorpo-rated minimum free energy information into the richly parameterized network, enhancing its robustness in predicting non-homologous RNA secondary structures. A Symmetric Argmax Post-processing algorithm ensures that GCNfold formulates valid structures. To validate our algo-rithm, we applied it to the SARS-CoV-2 E gene and determined the secondary structure of the E-gene across the Betacoronavirus subgenera. Biological sciences/Computational biology and bioinformatics/Machine learning Biological sciences/Molecular biology/Non-coding RNAs RNA Secondary Structure Graph Convolutional Neural Network Energy-based Model RNAfold SARS-CoV-2 Full Text Additional Declarations Yes there is potential Competing Interest. Dr. Roya Khosravi-Far is a Chief Executive Officer and Founder of the company InnoTech Precision Medicine. Dr. Dmitry Korkin was a consultant for the company Seismic Therapeutics. Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3798842","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":270235485,"identity":"7d9a142c-33c0-4c08-86ae-cf0e9088e7c4","order_by":0,"name":"Dmitry Korkin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtklEQVRIiWNgGAWjYDCCMwwMjA0GDHIgioGBjQQtxqRqYWBIbADziNHCd+bwsY8zCu6kb7jd3MDwoewwYS2SZ9uSZ24weJa74c7BBsYZ54jQYnCex5jxgcHh3G03EhuYedtI0JJuBtLylygtZ3uMGTcYHE4Aa2EkRovkmWPJjDMMDhvuB/rlYM+5dMJa+M4kH2bs+XNYXnJ2+8MHP8qsCWtBAAkGhgOkqIdoGQWjYBSMglGAFQAAdtBDk7Cz+vkAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-3875-9085","institution":"Worcester Polytechnic Institute","correspondingAuthor":true,"prefix":"","firstName":"Dmitry","middleName":"","lastName":"Korkin","suffix":""},{"id":270235486,"identity":"942c20e0-cf2a-4797-b792-dbb9281033a2","order_by":1,"name":"Aukkawut ammartayakun","email":"","orcid":"https://orcid.org/0000-0001-8680-4074","institution":"Worcester Polytechnic Institute","correspondingAuthor":false,"prefix":"","firstName":"Aukkawut","middleName":"","lastName":"ammartayakun","suffix":""},{"id":270235487,"identity":"39d355e0-5d1d-4987-bafa-5ea63273e595","order_by":2,"name":"Palawat Busaranuvong","email":"","orcid":"","institution":"Worcester Polytechnic Institute","correspondingAuthor":false,"prefix":"","firstName":"Palawat","middleName":"","lastName":"Busaranuvong","suffix":""},{"id":270235488,"identity":"5c5aa224-8761-4539-a0f1-eb5732375680","order_by":3,"name":"Roya Khosravi-Far","email":"","orcid":"","institution":"InnoTech Precision Medicine","correspondingAuthor":false,"prefix":"","firstName":"Roya","middleName":"","lastName":"Khosravi-Far","suffix":""}],"badges":[],"createdAt":"2023-12-24 04:30:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3798842/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3798842/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51529229,"identity":"73117623-f3f2-47b0-bb7b-cc1d4e002015","added_by":"auto","created_at":"2024-02-23 06:47:14","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3767641,"visible":true,"origin":"","legend":"Article File","description":"","filename":"GCNFoldmainmsFINAL.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3798842/v1_covered_818eb5e7-e092-4e1a-ac2d-471c84039b3a.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nDr. Roya Khosravi-Far is a Chief Executive Officer and Founder of the company InnoTech Precision Medicine. 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