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A new algorithm for multivariate genome wide association studies based on differential evolution and extreme learning machines

dc.contributor.authorÁlvarez Gutiérrez, David
dc.contributor.authorSánchez Lasheras, Fernando 
dc.contributor.authorMartín Sánchez, V.
dc.contributor.authorSuárez Gómez, Sergio Luis 
dc.contributor.authorMoreno, V.
dc.contributor.authorMoratalla Navarro, F.
dc.contributor.authorMolina de la Torre, A. J.
dc.date.accessioned2022-11-08T12:42:29Z
dc.date.available2022-11-08T12:42:29Z
dc.date.issued2022
dc.identifier.citationMathematics, 10(7) (2022); doi:10.3390/math10071024
dc.identifier.issn2227-7390
dc.identifier.urihttp://hdl.handle.net/10651/65324
dc.description.sponsorshipAgency for Management of University and Research Grants (AGAUR) of the Catalan Government [2017SGR723]; Instituto de Salud Carlos III; FEDER funds-a way to build Europe; Spanish Association Against Cancer (AECC) Scientific Foundation grant [GCTRA18022MORE]
dc.language.isoeng
dc.relation.ispartofMathematics
dc.rights© 2022 Los auotores
dc.rightsCC Reconocimiento 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85127603671&doi=10.3390%2fmath10071024&partnerID=40&md5=5ba0f04f3c93b91d8ed54d68a8ead3df
dc.titleA new algorithm for multivariate genome wide association studies based on differential evolution and extreme learning machines
dc.typejournal article
dc.identifier.doi10.3390/math10071024
dc.relation.publisherversionhttp://dx.doi.org/10.3390/math10071024
dc.rights.accessRightsopen access
dc.type.hasVersionVoR


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