Hadoop-Based Genome Comparisons

Author

Heinzlreiter, P. ; Krieger, M.T. ; Leitner, I.

Author_Institution

RISC Software GmbH, Hagenberg, Austria

fYear

2012

fDate

1-3 Nov. 2012

Firstpage

695

Lastpage

701

Abstract

Due to the ever increasing amounts of data in application areas relevant both for business and research, the requirements for data handling have increased significantly over the last years, often exceeding the capabilities of standard software, which has been used in specific application areas. To face this challenges software needs to be adapted or rewritten to integrate novel big data handling techniques. This paper focuses on the implementation of a genome sequence comparison application from the domain of bioinformatics running on top of Hadoop while relying on HBase for data management and MapReduce jobs for computation.

Keywords

bioinformatics; data handling; genomics; molecular biophysics; parallel processing; Hadoop-based genome comparison; MapReduce job; bioinformatics; data handling; data management; genome sequence comparison; software adaptation; software rewriting; Bioinformatics; Data handling; Data preprocessing; Data storage systems; Genomics; Information management; Runtime; BigData application; HBase; Hadoop; MapReduce; bioinformatics; genome comparison;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud and Green Computing (CGC), 2012 Second International Conference on

Conference_Location

Xiangtan

Print_ISBN

978-1-4673-3027-5

Type

conf

DOI

10.1109/CGC.2012.83

Filename

6382892