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dc.contributor.authorEl-Kalioby, Mohamed
dc.contributor.authorAbouelhoda, Mohamed
dc.contributor.authorKrüger, Jan
dc.contributor.authorGiegerich, Robert
dc.contributor.authorSczyrba, Alexander
dc.contributor.authorWall, Dennis Paul
dc.contributor.authorTonellato, Peter J
dc.date.accessioned2013-04-23T16:34:17Z
dc.date.issued2012
dc.identifier.citationEl-Kalioby, Mohamed, Mohamed Abouelhoda, Jan Krüger, Robert Giegerich, Alexander Sczyrba, Dennis Paul Wall, and Peter J. Tonellato. 2012. Personalized cloud-based bioinformatics services for research and education: Use cases and the elasticHPC package. BMC Bioinformatics 13(Suppl 17): S22.en_US
dc.identifier.issn1471-2105en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:10579553
dc.description.abstractBackground: Bioinformatics services have been traditionally provided in the form of a web-server that is hosted at institutional infrastructure and serves multiple users. This model, however, is not flexible enough to cope with the increasing number of users, increasing data size, and new requirements in terms of speed and availability of service. The advent of cloud computing suggests a new service model that provides an efficient solution to these problems, based on the concepts of "resources-on-demand" and "pay-as-you-go". However, cloud computing has not yet been introduced within bioinformatics servers due to the lack of usage scenarios and software layers that address the requirements of the bioinformatics domain. Results: In this paper, we provide different use case scenarios for providing cloud computing based services, considering both the technical and financial aspects of the cloud computing service model. These scenarios are for individual users seeking computational power as well as bioinformatics service providers aiming at provision of personalized bioinformatics services to their users. We also present elasticHPC, a software package and a library that facilitates the use of high performance cloud computing resources in general and the implementation of the suggested bioinformatics scenarios in particular. Concrete examples that demonstrate the suggested use case scenarios with whole bioinformatics servers and major sequence analysis tools like BLAST are presented. Experimental results with large datasets are also included to show the advantages of the cloud model. Conclusions: Our use case scenarios and the elasticHPC package are steps towards the provision of cloud based bioinformatics services, which would help in overcoming the data challenge of recent biological research. All resources related to elasticHPC and its web-interface are available at http://www.elasticHPC.org.en_US
dc.language.isoen_USen_US
dc.publisherBioMed Centralen_US
dc.relation.isversionofdoi:10.1186/1471-2105-13-S17-S22en_US
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521398/pdf/en_US
dash.licenseLAA
dc.titlePersonalized cloud-based bioinformatics services for research and education: Use cases and the elasticHPC packageen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalBMC Bioinformaticsen_US
dash.depositing.authorWall, Dennis Paul
dc.date.available2013-04-23T16:34:17Z
dc.identifier.doi10.1186/1471-2105-13-S17-S22*
dash.contributor.affiliatedWall, Dennis Paul
dash.contributor.affiliatedTonellato, Peter


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