@prefix this: <https://w3id.org/np/RANm9cS8je8mOTOqvtPvKZ_fZyBSXCDKeqQZvA1EwXZWo> .
@prefix sub: <https://w3id.org/np/RANm9cS8je8mOTOqvtPvKZ_fZyBSXCDKeqQZvA1EwXZWo/> .
@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 orcid: <https://orcid.org/> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .

<https://w3id.org/np/RANm9cS8je8mOTOqvtPvKZ_fZyBSXCDKeqQZvA1EwXZWo> a np:Nanopublication;
  np:hasAssertion sub:assertion;
  np:hasProvenance sub:provenance;
  np:hasPublicationInfo sub:pubinfo;
  dct:created "2026-02-18T21:24:58.546Z"^^xsd:dateTime;
  dct:creator orcid:0000-0002-1784-2920;
  dct:license <https://creativecommons.org/licenses/by/4.0/>;
  npx:introduces <http://purl.org/aida/Quantum%20approximate%20optimization%20algorithms%20outperform%20classical%20methods%20for%20disjoint%20network%20motif%20identification%20in%20biological%20networks.>;
  npx:supersedes <https://w3id.org/np/RAc4EIl-I7T5ny_-6Zx1p--X0bocq39nZJBAHFc_01SDg>;
  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/RAoTD7udB2KtUuOuAe74tJi1t3VzK0DyWS7rYVAq1GRvw>, <https://w3id.org/np/RAukAcWHRDlkqxk7H2XNSegc1WnHI569INvNr-xdptDGI>;
  nt:wasCreatedFromTemplate <https://w3id.org/np/RAmw2sp_oDePsdYg-7C8GCTMSzqAG2LFDe6NdRK0FwnQE> .

<http://purl.org/aida/Quantum%20approximate%20optimization%20algorithms%20outperform%20classical%20methods%20for%20disjoint%20network%20motif%20identification%20in%20biological%20networks.>
  a <https://w3id.org/sciencelive/o/terms/FORRT-Claim>, <https://w3id.org/sciencelive/o/terms/computational_performance-FORRT-Claim>;
  dct:source <https://doi.org/10.5281/zenodo.18157621>;
  nt:hasLabelFromApi "AIDA sentence: Quantum approximate optimization algorithms outperform classical methods for disjoint network motif ..." .

sub:assertion prov:wasAttributedTo orcid:0000-0002-1784-2920 .

orcid:0000-0002-1784-2920 foaf:name "Anne Fouilloux" .

sub:sig npx:hasAlgorithm "RSA";
  npx:hasPublicKey "MIGfMA0GCSqGSIb3DQEBAQUAA4GNADCBiQKBgQDWv2pJnmDsBOq8OlT1aSvYXSuWT34WOp4FYqEzdnn2F0kqzcFevBqWGZDxJWC0lqCrDEuNfp2QFyPe/+nES9dlHGYIhqPi68fwK6ZiNUotRFxXou+rjFznVvUxtCL8Ede79EBHwWN61QtwSIcU12bLoZsNPFlqQASQ93BJuKlihwIDAQAB";
  npx:hasSignature "TxIKJGWU2uyXoAwptf6KPgEWgVw6vRDQ10eckGSV2Zxgu9KEVKaNfl+wELZHH2prNfttm/8GaBBrSJpUr5XsdiBq4gbW8WuiUguddt4muNiTBnAS92qZCceruZ3L/nBmN8m3L2boMNBhgPgDQooW5/BuM5w8locI7ZzEs9H/Dq0=";
  npx:hasSignatureTarget <https://w3id.org/np/RANm9cS8je8mOTOqvtPvKZ_fZyBSXCDKeqQZvA1EwXZWo>;
  npx:signedBy orcid:0000-0002-1784-2920 .