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dc.contributor.authorMartínez Chamorro, Víctor Manuel 
dc.contributor.authorHermosilla Mechetti, Víctor Eduardo
dc.contributor.authorGómez Adorno, Helena
dc.contributor.authorPinto Roa, Diego Pedro 
dc.contributor.authorSchaerer Serra, Christian Emilio 
dc.contributor.authorDi Lella, Santiago
dc.contributor.authorColbes Sanabria, José Domingo 
dc.date.accessioned2026-05-19T19:03:20Z
dc.date.available2026-05-19T19:03:20Z
dc.date.issued2026-04-15
dc.identifier.citationMartínez, V., Hermosilla-Mechetti, V., Gomez-Adorno, H., Pinto-Roa, Diego P., Schaerer, C., Di Lella, S., & Colbes, J. (2026). Dataset of manually curated peptides against arthropod-borne viruses. Data in Brief, 66, 112765. https://doi.org/10.1016/j.dib.2026.112765en
dc.identifier.otherhttps://doi.org/10.1016/j.dib.2026.112765es
dc.identifier.urihttp://hdl.handle.net/20.500.14066/4780
dc.descriptionCorresponding author. E-mail address: jcolbes@pol.una.py (J. Colbes). Social media: @jcolbes (J. Colbes).en
dc.description.abstractAnti-arboviral peptides are biomolecules capable of interfering with key stages of the arboviral lifecycle. We present a dataset compiling 270 peptides composed of standard amino acids with reported activity against arboviruses, along with their lengths, sequences, target specificities, peptide entry mechanisms, and interaction mechanisms. The dataset was structured to support the training of machine learning models designed to identify anti-arboviral peptides. Therefore, it facilitates the development and validation of predictive tools against arboviruses. As a carefully assembled and expert-reviewed resource, this dataset aims to serve as a reference standard for evaluating new prediction models or comparing them with automatically compiled peptide datasets. This resource provides a comprehensive overview of the antiviral mechanisms currently being explored and can serve as a foundation for designing next-generation peptides targeting arboviral infections.es
dc.description.sponsorshipConsejo Nacional de Ciencia y Tecnologíaes
dc.format.extent11 páginases
dc.language.isoenges
dc.publisherElsevieres
dc.rightsAtribución/Reconocimiento-NoComercial 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subject.classification13. Avance general del conocimiento: I+D financiada con fuentes distintas a los FGUes
dc.subject.classification13.1. I+D relativa a las Ciencias Naturaleses
dc.subject.otherArboviruses
dc.subject.otherDatasetes
dc.subject.otherFlaviviruses
dc.subject.otherPeptideses
dc.subject.otherSequenceses
dc.titleDataset of manually curated peptides against arthropod-borne viruseses
dc.typeinfo:eu-repo/semantics/dataPaperes
dc.typeinfo:eu-repo/semantics/publishedVersiones
dc.identifier.doi10.1016/j.dib.2026.112765es
dc.description.fundingtextPrograma Paraguayo para el Desarrollo de la Ciencia y Tecnología. Proyectos de investigación y desarrolloes
dc.description.fundingtextPrograma Paraguayo para el Desarrollo de la Ciencia y Tecnología. Financiamiento de estancias de investigaciónes
dc.identifier.essn2352-3409es
dc.journal.titleData in Briefes
dc.relation.projectCONACYTPINV01-277es
dc.relation.projectCONACYTBINV04-101es
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.copyright© 2026 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).es
dc.subject.ocde1. Ciencias Naturaleses
dc.subject.ocde1.2. Ciencias Físicas (astronomía y ciencias del espacio, física, otras áreas afines)es
dc.volume.number66es
dc.relation.institBenefUniversidad Nacional de Asunción. Facultad Politécnicaes


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Atribución/Reconocimiento-NoComercial 4.0 Internacional
Except where otherwise noted, this item's license is described as Atribución/Reconocimiento-NoComercial 4.0 Internacional