CompLS - Runde 4 - Verbundprojekt: GENImmune - Generische Methoden zu Modellierung von Host-Pathogen Interaktionen angewandt zur eKizienten Immunisierung gegen SARS-CoV-2 - Teilprojekt E: Machine learning for epitope optimization
| dc.contributor.author | Frishman, Dmitrij | |
| dc.date.accessioned | 2025-11-05T12:07:57Z | |
| dc.date.available | 2025-11-05T12:07:57Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Datei-Upload durch TIB | ger |
| dc.description.version | publishedVersion | |
| dc.identifier.uri | https://oa.tib.eu/renate/handle/123456789/25617 | |
| dc.identifier.uri | https://doi.org/10.34657/24634 | |
| dc.language.iso | eng | |
| dc.publisher | Hannover : Technische Informationsbibliothek | |
| dc.relation.affiliation | Technische University München, School of Life Sciences, Department of Bioinformatics | |
| dc.rights.license | Creative Commons Attribution-NonDerivs 3.0 Germany | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nd/3.0/de/ | |
| dc.subject.ddc | 000 | Informatik, Information und Wissen, allgemeine Werke | |
| dc.title | CompLS - Runde 4 - Verbundprojekt: GENImmune - Generische Methoden zu Modellierung von Host-Pathogen Interaktionen angewandt zur eKizienten Immunisierung gegen SARS-CoV-2 - Teilprojekt E: Machine learning for epitope optimization | ger |
| dc.title.subtitle | Abschlussbericht 2024 | |
| dc.type | Report | |
| dc.type | Text | |
| dcterms.event.date | 01.01.2022-31.12.2023 | |
| dcterms.extent | 14 Seiten | |
| dtf.funding.funder | BMFTR | |
| dtf.funding.program | 031L0292E | |
| dtf.funding.verbundnummer | 01241688 | |
| tib.accessRights | openAccess |
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