Cloudflow – A Framework for MapReduce Pipeline Development in Biomedical Research (CROSBI ID 624576)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Forer, Lukas ; Afgan, Enis ; Weißensteiner, Hansi ; Davidović, Davor ; Specht, Gűnter ; Kronenberg, Florian ; Schönherr, Sebastian
engleski
Cloudflow – A Framework for MapReduce Pipeline Development in Biomedical Research
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.
Hadoop; biomedical; cloud; cloudflow; cloudman
Best paper award
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Podaci o prilogu
185-190.
2015.
objavljeno
Podaci o matičnoj publikaciji
MIPRO 2015 38th International Convention Proceedings
Petar Biljanović
Rijeka: Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO
978-953-233-083-0
Podaci o skupu
38. international convention on information and communication technology, electronics and microelectronics
predavanje
25.05.2015-29.05.2015
Opatija, Hrvatska