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dc.contributor.authorAnjum, Ashiq
dc.contributor.authorAizad, Sanna
dc.date.accessioned2019-12-13T12:03:34Z
dc.date.available2019-12-13T12:03:34Z
dc.date.issued2019
dc.identifier.citationAnjum, A., and Sanna, A. (2019) 'Graph data modelling for genomic variants', The 19th International Conference on Scalable Computing and Communications. De Montfort University, Leicester 19-23 August. New York: IEEE, pp. 1-8.en_US
dc.identifier.urihttp://hdl.handle.net/10545/624334
dc.description.abstractGenome variant analysis is performed on Variant Call Format (VCF) files. It can take days to process these files for genome analytics due to challenges such as loading the files for each user query and processing them to answer questions of interest. As data sizes grow, timely processing of this data is putting enormous pressure on the computational resources, leading to significant processing delays and may jeopardise the ultimate goal of bringing the genomic discoveries to masses. We believe this problem will not be solved until the underlying data structure to organise and process these files undergoes a transformation. To overcome this problem, we have proposed a graph based system to represent the data in VCF files. This allows the data to be loaded once in a graph model which is then subsequently queried and processed numerous times without any additional computational and data access penalties. This helps reduce data access time by giving a constant time access to any node and addresses performance and scalability challenges that have been a limiting factor for the mass scale adoption of genome analytics. It takes only 2ms to access any data node in our graph model and remains constant for any number of nodes.en_US
dc.description.sponsorshipUniversity of Derby, UKen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.urlhttp://www.smart-world.org/2019/scalcom/index.phpen_US
dc.relation.urlhttps://conferences.ieee.org/conferences_events/conferences/conferencedetails/46104en_US
dc.relation.urlhttps://ieeexplore.ieee.org/xpl/mostRecentWeeklyUpdatedConferencesIssues.jspen_US
dc.subjectgraph modelen_US
dc.subjectgenomeen_US
dc.subjectVariant Analysisen_US
dc.titleGraph data modelling for genomic variantsen_US
dc.typeArticleen_US
dc.typeMeetings and Proceedingsen_US
dc.contributor.departmentUniversity of Derbyen_US
dcterms.dateAccepted2019-07-01
dc.author.detail781847en_US


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