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dc.contributor.authorWert Carvajal, Carlos-
dc.contributor.authorSánchez García, Rubén-
dc.contributor.authorMacías, José R-
dc.contributor.authorSanz-Pamplona, Rebeca-
dc.contributor.authorMéndez Pérez, Almudena-
dc.contributor.authorAlemany Bonastre, Ramon-
dc.contributor.authorVeiga, Esteban-
dc.contributor.authorSorzano, Carlos Óscar S.-
dc.contributor.authorMuñoz Barrutia, Arrate-
dc.description.abstractLack of a dedicated integrated pipeline for neoantigen discovery in mice hinders cancer immunotherapy research. Novel sequential approaches through recurrent neural networks can improve the accuracy of T-cell epitope binding affinity predictions in mice, and a simplified variant selection process can reduce operational requirements. We have developed a web server tool (NAP-CNB) for a full and automatic pipeline based on recurrent neural networks, to predict putative neoantigens from tumoral RNA sequencing reads. The developed software can estimate H-2 peptide ligands, with an AUC comparable or superior to state-of-the-art methods, directly from tumor samples. As a proof-of-concept, we used the B16 melanoma model to test the system's predictive capabilities, and we report its putative neoantigens. NAP-CNB web server is freely available at with scripts and datasets accessible through the download section.-
dc.format.extent10 p.-
dc.publisherSpringer Science and Business Media LLC-
dc.relation.isformatofReproducció del document publicat a:
dc.relation.ispartofScientific Reports, 2021, vol. 11, num. 10780-
dc.rightscc by (c) Wert Carvajal, Carlos et al., 2021-
dc.subject.classificationCèl·lules T-
dc.subject.otherT cells-
dc.titlePredicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool-
Appears in Collections:Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))

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