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dc.contributor.authorParnas Gulnes, Maren
dc.contributor.authorSoylu, Ahmet
dc.contributor.authorRoman, Dumitru
dc.identifier.citationData Technologies and Applications. 2021, .en_US
dc.description.abstractPurpose: Neuroscience data is spread across a variety of sources, typically provisioned through ad-hoc and non-standard approaches and formats, and often has no connection to the related data sources. These make it difficult for researchers to understand, integrate, and reuse brain-related data. The aim of this study is to show that a graph-based approach offers an effective mean for representing, analysing, and accessing brain-related data, which is highly interconnected, evolving over time, and often needed in combination. Approach: We present an approach for organising brain-related data in a graph model. The approach is exemplified in the case of a unique data set of quantitative neuroanatomical data about the murine basal ganglia — a group of nuclei in the brain essential for processing information related to movement. Specifically, the murine basal ganglia data set is modelled as a graph, integrated with relevant data from third-party repositories, published through a Web-based user interface and API, analysed from exploratory and confirmatory perspectives using popular graph algorithms to extract new insights. Findings: The evaluation of the graph model and the results of the graph data analysis and usability study of the user interface suggest that graph-based data management in the neuroscience domain is a promising approach, since it enables integration of various disparate data sources, and improves understanding and usability of data. Originality: The study provides a practical and generic approach for representing, integrating, analysing, and provisioning brain-related data, and a set of software tools to support the proposed approach.en_US
dc.description.sponsorshipThis work was partly funded by the EC H2020 DataCloud project (Grant number 101016835).en_US
dc.relation.ispartofseriesData Technologies and Applications;
dc.rightsNavngivelse-Ikkekommersiell 4.0 Internasjonal*
dc.subjectGraph databasesen_US
dc.subjectBrain-related dataen_US
dc.subjectMurine basal gangliaen_US
dc.subjectData integrationen_US
dc.subjectData analyticsen_US
dc.titleA graph-based approach for representing, integrating and analysing neuroscience data: the case of the murine basal gangliaen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalData Technologies and Applicationsen_US
dc.relation.projectHorisont 2020: EC/H2020/101016835en_US

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Navngivelse-Ikkekommersiell 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse-Ikkekommersiell 4.0 Internasjonal