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Skalabilna softverska platforma za pretraživanje hemijskih i bioloških repozitorijuma

dc.contributor.advisorMilentijević, Ivan
dc.contributor.otherRančić, Dejan
dc.contributor.otherStoimenov, Leonid
dc.contributor.otherTošić, Milorad
dc.contributor.otherBašić, Milan
dc.creatorArsić, Branko J.
dc.date.accessioned2021-03-23T10:02:20Z
dc.date.available2021-03-23T10:02:20Z
dc.date.issued2020-10-12
dc.identifier.urihttp://eteze.ni.ac.rs/application/showtheses?thesesId=7961
dc.identifier.urihttps://fedorani.ni.ac.rs/fedora/get/o:1679/bdef:Content/download
dc.identifier.urihttp://vbs.rs/scripts/cobiss?command=DISPLAY&base=70052&RID=25058825
dc.identifier.urihttps://nardus.mpn.gov.rs/handle/123456789/18141
dc.descriptionThis dissertation is about the SpecINT (Spectral Integration), a scalable software platform, which benefits from the Semantic Web and from the results of spectral graph theory for data integration and exploring semanticbased repositories. In order to save time and resources, institutions are in need of a comprehensive overview of relevant and most recently published data globally. According to statistics, only one substance out of thousands satisfies the preclinical and clinical tests’ criteria and can be used as a medicament. Laboratory conditions require a lot of time and resources to test the effect of large number of substances, and that is why application of in silico models is found necessary. The methodology applied to achieve this goal is based on the coordinates of graph eigenvectors used for automatic join of sub-queries in Federated SPARQL query out of which only the most relevant data sources within repositories are taken into consideration. Such an approach enables reduction of number of duplicates in the results obtained, but also provides useful results for the researchers. In this way the integration of repositories can be effected without a common ontology between them, leaving an impression there exists a searchable central and virtual storage. The platform is developed in collaboration with the Laboratory for Cell and Molecular Biology of the Faculty of Science, University of Kragujevac. However, the methodology can be applied more broadly, since it is based on the „Open Data” standards and concepts.en
dc.formatapplication/pdf
dc.languagesr
dc.publisherУниверзитет у Нишу, Електронски факултетsr
dc.relationinfo:eu-repo/grantAgreement/MESTD/Integrated and Interdisciplinary Research (IIR or III)/41010/RS//
dc.relationinfo:eu-repo/grantAgreement/MESTD/Integrated and Interdisciplinary Research (IIR or III)/44006/RS//
dc.relationinfo:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/174033/RS//
dc.rightsopenAccessen
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.sourceУниверзитет у Нишуsr
dc.subjectIntegracija repozitorijumasr
dc.subjectData integrationen
dc.subjectSemantički Vebsr
dc.subjectsoftverska platformasr
dc.subjectspektralna klasterizacijasr
dc.subjectteorija grafovasr
dc.subjectSemantic Weben
dc.subjectsoftware platformen
dc.subjectspectral clusteringen
dc.subjectgraph theoryen
dc.titleSkalabilna softverska platforma za pretraživanje hemijskih i bioloških repozitorijumasr
dc.typePhD thesis
dc.rights.licenseBY-NC
dcterms.abstractМилентијевић, Иван; Башић, Милан; Тошић, Милорад; Стоименов, Леонид; Ранчић, Дејан; Aрсић, Бранко Ј.; Скалабилна софтверска платформа за претраживање хемијских и биолошких репозиторијума; Скалабилна софтверска платформа за претраживање хемијских и биолошких репозиторијума;
dc.identifier.fulltexthttps://nardus.mpn.gov.rs/bitstream/id/70340/Disertacija.pdf
dc.identifier.fulltexthttps://nardus.mpn.gov.rs/bitstream/id/70341/Arsic_Branko_J.pdf
dc.identifier.rcubhttps://hdl.handle.net/21.15107/rcub_nardus_18141


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Приказ основних података о дисертацији