NDLI: Improving the Performance of Biological Data Analysis in Cloud Computing Platforms

Content Provider	IEEE Xplore Digital Library
Author	Tonini, G. Siqueira, F.
Copyright Year	2015
Description	Author affiliation: Dept. of Inf. & Stat., Fed. Univ. of Santa Catarina, Florianopolis, Brazil (Tonini, G.; Siqueira, F.)
Abstract	The adoption of distributed database architectures for processing large data sets has shown to be an effective approach to reduce the response time of data analysis procedures. The same approach may be adopted on biological databases, which comprise vast amounts of data that are analyzed to detect genetic diseases, to understand their causing factors and to design process-blocking substances. Defining how data will be fragmented over several network nodes, though, is a non-trivial task. In this work, we have applied a recently proposed methodology for distributed data allocation to create several topology scenarios in a cloud computing infrastructure aiming to improve the performance of data analysis procedures. The proposed scenarios were evaluated using modMine, which is an instance of the Intermine Data warehouse, as case study.
Starting Page	766
Ending Page	772
File Size	439146
Page Count	7
File Format	PDF
ISSN	21596190
e-ISBN	9781467372879
DOI	10.1109/CLOUD.2015.106
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Cloud computing Distributed databases Parallel processing Biology Biological databases Resource management Indexes Data allocation strategies
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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