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An Efficient Feature Extraction Method for Identifying Signatures of Viral Genomic Variants

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datacite.subject.fosCiências Médicas::Biotecnologia Médica
datacite.subject.fosEngenharia e Tecnologia::Outras Engenharias e Tecnologias
datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg04:Educação de Qualidade
dc.contributor.authorSouza, Felipe Bueno de
dc.contributor.authorPimenta-Zanon, Matheus Henrique
dc.contributor.authorHenriques, Dora
dc.contributor.authorPinto, M. Alice
dc.contributor.authorBalsa, Carlos
dc.contributor.authorRufino, José
dc.contributor.authorLopes, Fabrício Martins
dc.date.accessioned2026-06-24T10:32:57Z
dc.date.available2026-06-24T10:32:57Z
dc.date.issued2026
dc.description.abstractGenomic analysis is a powerful way to understand viral pathogens and their variations. However, most of the genomic analysis methods are based on sequence alignment, which has a high computational cost. This study introduces a novel methodology to extract discriminative regions from viral genomes. Using exclusive k-mers through strategically defined sliding windows, our approach identifies genomic regions with high concentrations of variant-specific signatures, showcasing high-accuracy classification while requiring modest computational resources. The data-driven and nonparametric nature of our approach enables pattern extraction without imposing predefined distributions, enhancing both analytical flexibility and result interpretability. By balancing minimal k-mer sizes with maximum discriminative power, our method achieves remarkable generalization capability even with limited training samples. The computational efficiency of the methodology alongside the biological transparency and explainability in the results makes it accessible to research environments with restricted processing capacity, potentially accelerating genomic signature discovery across diverse viral pathogens and contributing to better variant tracking and characterization, thus opening up even more possibilities in genomic analysis studies.eng
dc.description.sponsorshipThis work was supported by national funds: UID/05757 -Research Centre in Digitalization and Intelligent Robotics (CeDRI); and SusTEC,LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020); and Fundação Araucária(Grants 035/2019, 138/2021 and NAPI-Bioinformática), CNPq 440412/2022-6 and 408312/2023-8), CIMO UID/00690/2025 (10.54499/UID/00690/2025) and UID/PRR/00690/2025 (10.54499/UIPRR/00690/2025).
dc.identifier.citationSouza, Felipe Bueno de; Pimenta-Zanon, Matheus Henrique; Henriques, Dora; Pinto, M. Alice; Balsa, Carlos; Lopes, Fabrício Martins (2026). An Efficient Feature Extraction Method for Identifying Signatures of Viral Genomic Variants. In 15 International workshop on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2025. Cartagena de Indias: Springer Deutschland GmbH. p. 48-62. ISBN 978-303216847-4
dc.identifier.doi10.1007/978-3-032-16848-1_4
dc.identifier.isbn978303216847-4
dc.identifier.issn1865-0929
dc.identifier.urihttp://hdl.handle.net/10198/36927
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer
dc.relationCentro de Investigação em Digitalização e Robótica Inteligente - UID/PRR/05757/2025
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
dc.relationCIMO - Mountain Research Center - UID/PRR/00690/2025
dc.relationMountain Research Center - UID/00690/2025
dc.relation.ispartofCommunications in Computer and Information Science
dc.relation.ispartofAdvanced Research in Technologies, Information, Innovation and Sustainability
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectViral genomics
dc.subjectk-mer analysis
dc.subjectFeature extraction
dc.subjectSARS-CoV-2
dc.subjectComputational efficiency
dc.subjectDiscriminative regions
dc.subjectGenomic signatures
dc.subjectAlignment-free analysis
dc.subjectData-driven
dc.subjectNon-parametric modeling
dc.titleAn Efficient Feature Extraction Method for Identifying Signatures of Viral Genomic Variantseng
dc.typeconference paper
dspace.entity.typePublication
oaire.awardNumberUID/PRR/05757/2025
oaire.awardNumberLA/P/0007/2020
oaire.awardNumberUID/PRR/00690/2025
oaire.awardNumberUID/00690/2025
oaire.awardTitleCentro de Investigação em Digitalização e Robótica Inteligente - UID/PRR/05757/2025
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
oaire.awardTitleCIMO - Mountain Research Center - UID/PRR/00690/2025
oaire.awardTitleMountain Research Center - UID/00690/2025
oaire.awardURIhttps://doi.org/10.54499/UID/PRR/05757/2025
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.awardURIhttp://hdl.handle.net/10198/36356
oaire.awardURIhttp://hdl.handle.net/10198/35759
oaire.citation.conferenceDate2026
oaire.citation.conferencePlaceCartagena de Indias
oaire.citation.endPage62
oaire.citation.startPage48
oaire.citation.title15 International workshop on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2025
oaire.fundingStreamAvaliação UID 2023/2024 PRR
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStreamCIMO
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameHenriques
person.familyNamePinto
person.familyNameBalsa
person.familyNameRufino
person.givenNameDora
person.givenNameM. Alice
person.givenNameCarlos
person.givenNameJosé
person.identifier1721518
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person.identifier.ciencia-idC414-F47F-6323
person.identifier.orcid0000-0001-7530-682X
person.identifier.orcid0000-0001-9663-8399
person.identifier.orcid0000-0003-2431-8665
person.identifier.orcid0000-0002-1344-8264
person.identifier.ridM-8735-2013
person.identifier.scopus-author-id55761737300
person.identifier.scopus-author-id8085507800
person.identifier.scopus-author-id23391719100
person.identifier.scopus-author-id55947199100
project.funder.identifierhttp://doi.org/10.13039/501100001871
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project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
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