Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/1319
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dc.contributor.authorVeljković, Aleksandar Nen_US
dc.contributor.authorOrlov, Yuriy Len_US
dc.contributor.authorMitić, Nenaden_US
dc.date.accessioned2024-07-12T15:39:33Z-
dc.date.available2024-07-12T15:39:33Z-
dc.date.issued2023-04-09-
dc.identifier.issn16616596-
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/1319-
dc.descriptionInt. J. Mol. Sci. 2023, 24(8), 6954; https://doi.org/10.3390/ijms24086954en_US
dc.description.abstractStudying the association of gene function, diseases, and regulatory gene network reconstruction demands data compatibility. Data from different databases follow distinct schemas and are accessible in heterogenic ways. Although the experiments differ, data may still be related to the same biological entities. Some entities may not be strictly biological, such as geolocations of habitats or paper references, but they provide a broader context for other entities. The same entities from different datasets can share similar properties, which may or may not be found within other datasets. Joint, simultaneous data fetching from multiple data sources is complicated for the end-user or, in many cases, unsupported and inefficient due to differences in data structures and ways of accessing the data. We propose BioGraph-a new model that enables connecting and retrieving information from the linked biological data that originated from diverse datasets. We have tested the model on metadata collected from five diverse public datasets and successfully constructed a knowledge graph containing more than 17 million model objects, of which 2.5 million are individual biological entity objects. The model enables the selection of complex patterns and retrieval of matched results that can be discovered only by joining the data from multiple sources.en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.relation.ispartofInternational journal of molecular sciencesen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subjectBioGraphen_US
dc.subjectassociations with the diseasesen_US
dc.subjectconnecting biological dataen_US
dc.subjectgene networken_US
dc.subjectmetadataen_US
dc.subjectquery data propertiesen_US
dc.titleBioGraph: Data Model for Linking and Querying Diverse Biological Metadataen_US
dc.typeArticleen_US
dc.identifier.doi10.3390/ijms24086954-
dc.identifier.pmid37108117-
dc.identifier.scopus2-s2.0-85156086870-
dc.identifier.isi000977569100001-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85156086870-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.relation.issn1422-0067en_US
dc.description.rankM21en_US
dc.relation.firstpageArticle no. 6954en_US
dc.relation.volume24en_US
dc.relation.issue8en_US
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.openairetypeArticle-
crisitem.author.deptInformatics and Computer Science-
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