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Cloudflow – A Framework for MapReduce Pipeline Development in Biomedical Research

Forer, Lukas; Afgan, Enis; Weißensteiner, Hansi; Davidović, Davor; Specht, Gűnter; Kronenberg, Florian; Schönherr, Sebastian (2015) Cloudflow – A Framework for MapReduce Pipeline Development in Biomedical Research. In: 38. international convention on information and communication technology, electronics and microelectronics (25 May 2015 - 29 May 2015) Opatija, Hrvatska.

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Abstract

The data-driven parallelization framework Hadoop MapReduce allows analysing large data sets in a scalable way. Since the development of MapReduce programs can be a time-intensive and challenging task, the application and usage of Hadoop in Biomedical Research is still limited. Here we resent Cloudflow, a high-level framework to hide the implementation details of Hadoop and to provide a set of building blocks to create biomedical pipelines in a more intuitive way. We demonstrate the benefit of Cloudflow on three different genetic use cases. It will be shown how the framework can be combined with the Hadoop workflow system Cloudgene and the cloud orchestration platform CloudMan to provide Hadoop pipelines as a service to everyone.

Item Type: Conference or workshop item published in conference proceedings (UNSPECIFIED)
Uncontrolled Keywords: Hadoop; biomedical; cloud; cloudflow; cloudman
Subjects: NATURAL SCIENCES > Biology > Genetics, Evolution and Phylogenetics
TECHNICAL SCIENCES > Computing
BIOMEDICINE AND HEALTHCARE
Divisions: Center for Informatics and Computing
Projects:
Project titleProject leaderProject codeProject type
Scalable Big Data Bioinformatics Analysis in the CloudEnis AfganUNSPECIFIEDBilateralni projekt
Depositing User: Davor Davidović
Date Deposited: 01 Jun 2015 10:11
Last Modified: 29 Sep 2015 14:39
URI: http://fulir.irb.hr/id/eprint/1988

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