GI LogoGI Logo
  • Login
Digital Library
    • All of DSpace

      • Communities & Collections
      • Titles
      • Authors
      • By Issue Date
      • Subjects
    • This Collection

      • Titles
      • Authors
      • By Issue Date
      • Subjects
Digital Library Gesellschaft für Informatik e.V.
GI-DL
    • English
    • Deutsch
  • English 
    • English
    • Deutsch
View Item 
  •   DSpace Home
  • Lecture Notes in Informatics
  • Proceedings
  • BTW - Datenbanksysteme für Business, Technologie und Web
  • P265 - BTW2017 - Datenbanksysteme für Business, Technologie und Web
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
  •   DSpace Home
  • Lecture Notes in Informatics
  • Proceedings
  • BTW - Datenbanksysteme für Business, Technologie und Web
  • P265 - BTW2017 - Datenbanksysteme für Business, Technologie und Web
  • View Item

Efficient Storage and Analysis of Genome Data in Databases

Author:
Dorok, Sebastian [DBLP] ;
Breß, Sebastian [DBLP] ;
Teubner, Jens [DBLP] ;
Läpple, Horstfried [DBLP] ;
Saake, Gunter [DBLP] ;
Markl, Volker [DBLP]
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 = {}
}
DateienGroesseFormatAnzeige
paper28.pdf640.0Kb PDF View/Open

Haben Sie fehlerhafte Angaben entdeckt? Sagen Sie uns Bescheid: Send Feedback

More Info

ISBN: 978-3-88579-659-6
ISSN: 1617-5468
xmlui.MetaDataDisplay.field.date: 2017
Language: en (en)
Content Type: Text/Conference Paper

Keywords

  • main-memory database systems
  • genome analysis
  • variant calling
Collections
  • P265 - BTW2017 - Datenbanksysteme für Business, Technologie und Web [56]

Show full item record


About uns | FAQ | Help | Imprint | Datenschutz

Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.

 

 


About uns | FAQ | Help | Imprint | Datenschutz

Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.