Efficient Storage and Analysis of Genome Data in Databases
Abstract
Genome-analysis enables researchers to detect mutations within genomes and deduce their consequences. Researchers need reliable analysis platforms to ensure reproducible and comprehensive analysis results. Database systems provide vital support to implement the required sustainable procedures. Nevertheless, they are not used throughout the complete genome-analysis process, because (1) database systems su er from high storage overhead for genome data and (2) they introduce overhead during domain-specific analysis. To overcome these limitations, we integrate genome-specific compression into database systems using a specialized database schema. Thus, we can reduce the storage overhead to 30%. Moreover, we can exploit genome-data characteristics during query processing allowing us to analyze real-world data sets up to five times faster than specialized analysis tools and eight times faster than a straightforward database approach.
- Citation
- BibTeX
Dorok, S., Breß, S., Teubner, J., Läpple, H., Saake, G. & Markl, V.,
(2017).
Efficient Storage and Analysis of Genome Data in Databases.
In:
Mitschang, B., Nicklas, D., Leymann, F., Schöning, H., Herschel, M., Teubner, J., Härder, T., Kopp, O. & Wieland, M.
(Hrsg.),
Datenbanksysteme für Business, Technologie und Web (BTW 2017).
Gesellschaft für Informatik, Bonn.
(S. 423-442).
@inproceedings{mci/Dorok2017,
author = {Dorok, Sebastian AND Breß, Sebastian AND Teubner, Jens AND Läpple, Horstfried AND Saake, Gunter AND Markl, Volker},
title = {Efficient Storage and Analysis of Genome Data in Databases},
booktitle = {Datenbanksysteme für Business, Technologie und Web (BTW 2017)},
year = {2017},
editor = {Mitschang, Bernhard AND Nicklas, Daniela AND Leymann, Frank AND Schöning, Harald AND Herschel, Melanie AND Teubner, Jens AND Härder, Theo AND Kopp, Oliver AND Wieland, Matthias} ,
pages = { 423-442 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
author = {Dorok, Sebastian AND Breß, Sebastian AND Teubner, Jens AND Läpple, Horstfried AND Saake, Gunter AND Markl, Volker},
title = {Efficient Storage and Analysis of Genome Data in Databases},
booktitle = {Datenbanksysteme für Business, Technologie und Web (BTW 2017)},
year = {2017},
editor = {Mitschang, Bernhard AND Nicklas, Daniela AND Leymann, Frank AND Schöning, Harald AND Herschel, Melanie AND Teubner, Jens AND Härder, Theo AND Kopp, Oliver AND Wieland, Matthias} ,
pages = { 423-442 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
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More Info
ISBN: 978-3-88579-659-6
ISSN: 1617-5468
xmlui.MetaDataDisplay.field.date: 2017
Language:
(en)

Content Type: Text/Conference Paper