Graphical Approach to Unveil Evolutionary Relationship from DNA Sequence Analysis

preprint OA: closed CC-BY-4.0
📄 Open PDF Full text JSON View at publisher

Abstract

Graph theory is an efficient bioinformatics approach that offers a methodical approach to modelling and evaluating complex biological data. In this work graph theory was utilized for comparing DNA sequences. Each DNA sequence was break up into nucleotide couples, from which weighted loop digraphs with sixteen vertices was constructed. To assess the sequence similarity distance metrics like Cosine, Correlation, and Jaccard were employed. Nucleotides fragments of 1 different species were examined to confirm the methodology. This research elucidate as an effective tool graph theory is applied for sequence comparison and investigation of biological data in the field of bioinformatics.
Full text 10,130 characters · extracted from preprint-html · click to expand
Graphical Approach to Unveil Evolutionary Relationship from DNA Sequence Analysis | 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 Research Article Graphical Approach to Unveil Evolutionary Relationship from DNA Sequence Analysis Riaz Hussain Khan, Nadeem Salamat, Amr Yousef, A. Q. Baig, Zaffar Ahmed Shaikh, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3953357/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Graph theory is an efficient bioinformatics approach that offers a methodical approach to modelling and evaluating complex biological data. In this work graph theory was utilized for comparing DNA sequences. Each DNA sequence was break up into nucleotide couples, from which weighted loop digraphs with sixteen vertices was constructed. To assess the sequence similarity distance metrics like Cosine, Correlation, and Jaccard were employed. Nucleotides fragments of 1 different species were examined to confirm the methodology. This research elucidate as an effective tool graph theory is applied for sequence comparison and investigation of biological data in the field of bioinformatics. DNA Sequences comparison Phylogenetic tree Alignment-free method Graphical method Evolutionary relationship Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3953357","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":273295441,"identity":"971191ff-7355-4616-a0eb-35a6b23add7e","order_by":0,"name":"Riaz Hussain Khan","email":"","orcid":"","institution":"Khwaja Fareed University of Engineering and Information Technology","correspondingAuthor":false,"prefix":"","firstName":"Riaz","middleName":"Hussain","lastName":"Khan","suffix":""},{"id":273295442,"identity":"9ba3ff8c-236e-431b-b537-5a0e4864d226","order_by":1,"name":"Nadeem Salamat","email":"data:image/png;base64,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","orcid":"","institution":"Khwaja Fareed University of Engineering and Information Technology","correspondingAuthor":true,"prefix":"","firstName":"Nadeem","middleName":"","lastName":"Salamat","suffix":""},{"id":273295443,"identity":"d3a771b2-4511-4053-8e77-25e2747ee180","order_by":2,"name":"Amr Yousef","email":"","orcid":"","institution":"University of Business and Technology","correspondingAuthor":false,"prefix":"","firstName":"Amr","middleName":"","lastName":"Yousef","suffix":""},{"id":273295444,"identity":"3cd7f78c-5dd9-4171-a0a5-e6fc1c4d4944","order_by":3,"name":"A. Q. Baig","email":"","orcid":"","institution":"Institute of Southern Punjab","correspondingAuthor":false,"prefix":"","firstName":"A.","middleName":"Q.","lastName":"Baig","suffix":""},{"id":273295445,"identity":"f451dc6f-c14c-4169-aed1-aed5f83da770","order_by":4,"name":"Zaffar Ahmed Shaikh","email":"","orcid":"","institution":"Department of Computer Science and Information Technology, Benazir Bhutto Shaheed University Lyari,","correspondingAuthor":false,"prefix":"","firstName":"Zaffar","middleName":"Ahmed","lastName":"Shaikh","suffix":""},{"id":273295446,"identity":"ba8b740b-7263-4ea1-9921-8c18b89b4975","order_by":5,"name":"Alexey Mikhaylov","email":"","orcid":"","institution":"Financial University","correspondingAuthor":false,"prefix":"","firstName":"Alexey","middleName":"","lastName":"Mikhaylov","suffix":""}],"badges":[],"createdAt":"2024-02-13 11:02:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3953357/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3953357/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51384813,"identity":"b9acb33b-899a-405e-ad0e-ae82f399984d","added_by":"auto","created_at":"2024-02-20 17:06:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":778364,"visible":true,"origin":"","legend":"","description":"","filename":"NadeemBMC.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3953357/v1_covered_4284074d-0423-482e-91ba-a4542f34bb6b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Graphical Approach to Unveil Evolutionary Relationship from DNA Sequence Analysis","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"DNA Sequences comparison, Phylogenetic tree, Alignment-free method, Graphical method, Evolutionary relationship","lastPublishedDoi":"10.21203/rs.3.rs-3953357/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3953357/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Graph theory is an efficient bioinformatics approach that offers a methodical approach to modelling and evaluating complex biological data. In this work graph theory was utilized for comparing DNA sequences. Each DNA sequence was break up into nucleotide couples, from which weighted loop digraphs with sixteen vertices was constructed. To assess the sequence similarity distance metrics like Cosine, Correlation, and Jaccard were employed. Nucleotides fragments of 1 different species were examined to confirm the methodology. This research elucidate as an effective tool graph theory is applied for sequence comparison and investigation of biological data in the field of bioinformatics.","manuscriptTitle":"Graphical Approach to Unveil Evolutionary Relationship from DNA Sequence Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-20 06:44:29","doi":"10.21203/rs.3.rs-3953357/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2fe03da8-4627-4ef1-9211-61e5a73b2eeb","owner":[],"postedDate":"February 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-02-20T17:06:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-20 06:44:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3953357","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3953357","identity":"rs-3953357","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2024) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
unpaywall
last seen: 2026-05-29T02:00:03.542394+00:00
License: CC-BY-4.0