https://w3id.org/np/RAQvZ04s6dpC3g0NwQ9CV3kEB7EVqcDvSUPQdjVnHmS8U
.trig | .trig.txt | .jelly | .jelly.txt | .jsonld | .jsonld.txt | .nq | .nq.txt | .xml | .xml.txt
@prefix this: <https://w3id.org/np/RAQvZ04s6dpC3g0NwQ9CV3kEB7EVqcDvSUPQdjVnHmS8U> . @prefix sub: <https://w3id.org/np/RAQvZ04s6dpC3g0NwQ9CV3kEB7EVqcDvSUPQdjVnHmS8U/> . @prefix np: <http://www.nanopub.org/nschema#> . @prefix dct: <http://purl.org/dc/terms/> . @prefix nt: <https://w3id.org/np/o/ntemplate/> . @prefix npx: <http://purl.org/nanopub/x/> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix orcid: <https://orcid.org/> . @prefix prov: <http://www.w3.org/ns/prov#> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . sub:Head { this: a np:Nanopublication; np:hasAssertion sub:assertion; np:hasProvenance sub:provenance; np:hasPublicationInfo sub:pubinfo . } sub:assertion { <https://osf.io/92snx> dct:issued "July 2025"; dct:license <http://purl.org/np/RAQ__sGdY_Qc7l1O_zmn4nr-pMBOxKU04Ur9s998rS6Fc#CC-BY-4.0>; <https://w3id.org/fdof/ontology#hasEncodingFormat> <https://www.iana.org/assignments/media-types/application/pdf>; <https://w3id.org/fdof/ontology#materializes> sub:STAYAHEAD_DA1; <https://www.w3.org/ns/dcat#accessURL> <https://osf.io/download/92snx/> . sub:STAYAHEAD_DA1 a <https://w3id.org/fair/ff/terms/article>, <https://w3id.org/fdof/ontology#FAIRDigitalObject>; dct:contributor orcid:0000-0001-7871-2073, orcid:0000-0001-8888-635X; dct:creator orcid:0009-0004-2188-0817; dct:hasVersion "1.0.0"; dct:isPartOf <https://w3id.org/np/RAz72LNwv9hNpTiQICSUAbaMYnTXV0HmBsD31W1MtWoYY>; dct:language <https://www.omg.org/spec/LCC/Languages/LaISO639-1-LanguageCodes/en>; dct:publisher <https://ror.org/027bh9e22>; dct:subject <http://aims.fao.org/aos/agrovoc/c_4318>; rdfs:comment "This article presents an extended dataset description and methodology behind a large number of theoretical and empirical SARS-CoV-2 spike receptor-binding domain (RBD) variants, developed under the STAYAHEAD project for pandemic preparedness. It integrates large-scale in silico structure predictions with empirical biophysical measurements."; rdfs:label "Structure-Based Prediction of SARS-CoV-2 Variant Properties Using Machine Learning on Mutational Neighborhoods"; <https://schema.org/funder> <https://ror.org/056cwr036>; <https://w3id.org/fdof/ontology#hasMetadata> this:; <https://www.w3.org/ns/dcat#contactPoint> "e.a.schultes@lacdr.leidenuniv.nl"; <https://www.w3.org/ns/dcat#endDate> "July 2025"; <https://www.w3.org/ns/dcat#startDate> "March 2023" . } sub:provenance { sub:assertion prov:wasAttributedTo orcid:0000-0001-8888-635X . } sub:pubinfo { <http://purl.org/np/RAQ__sGdY_Qc7l1O_zmn4nr-pMBOxKU04Ur9s998rS6Fc#CC-BY-4.0> nt:hasLabelFromApi "CC BY 4.0 | Attribution 4.0 International - Using this licence you are free to share and adapt the resource but you must ..." . orcid:0000-0001-8888-635X foaf:name "Erik Schultes" . this: dct:created "2025-07-13T14:30:56.032Z"^^xsd:dateTime; dct:creator orcid:0000-0001-8888-635X; dct:license <https://creativecommons.org/licenses/by/4.0/>; npx:introduces sub:STAYAHEAD_DA1; npx:wasCreatedAt <https://nanodash.knowledgepixels.com/>; nt:wasCreatedFromProvenanceTemplate <https://w3id.org/np/RA7lSq6MuK_TIC6JMSHvLtee3lpLoZDOqLJCLXevnrPoU>; nt:wasCreatedFromPubinfoTemplate <https://w3id.org/np/RA0J4vUn_dekg-U1kK3AOEt02p9mT2WO03uGxLDec1jLw>, <https://w3id.org/np/RAukAcWHRDlkqxk7H2XNSegc1WnHI569INvNr-xdptDGI>; nt:wasCreatedFromTemplate <https://w3id.org/np/RArM5GTwgxg9qslGX-XiQ-KTTUwdoM0KB1YqmT4GqTizA> . sub:sig npx:hasAlgorithm "RSA"; npx:hasPublicKey "MIGfMA0GCSqGSIb3DQEBAQUAA4GNADCBiQKBgQCK1HbLXqu6lKnelVTcHiTVw07+CR5R3LvTsWDcyRgnvE8vHmlcNjc/Yj9cbEIidzqLHS00/LYxPV8lsCqO4DnRETGuq/ompAGXWP/xTLClQBm1uRUYsLq/GAcu/TPsXaGMJBTiBiGByLE4eiDQucLkRjLmAfA7X4QIgl4fgK1udQIDAQAB"; npx:hasSignature "a4TVK46ZbxE53wjH+OtNjsqJ9I98VbZlLk0z6CTtqd3MUVajVj8motLMHIgixYyNAq2TC6oAHLaOuIKnuyRYL+q7ycXGKxy2kU2RwyjuNEXMMf23gbgKR+GHf4aYci4qGfd/G6RURzn17fbuNrenFgVM4D0m+oY6HOnbcZeQ4Bk="; npx:hasSignatureTarget this:; npx:signedBy orcid:0000-0001-8888-635X . }