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This article is part of the supplement: Eleventh International Conference on Bioinformatics (InCoB2012): Bioinformatics

Open Access Proceedings

Personalized cloud-based bioinformatics services for research and education: use cases and the elasticHPC package

Mohamed El-Kalioby1*, Mohamed Abouelhoda12*, Jan Krüger3, Robert Giegerich3, Alexander Sczyrba3, Dennis P Wall4 and Peter Tonellato4*

Author Affiliations

1 Centre for Informatics Sciences, Nile University, Giza, Egypt

2 Faculty of Engineering, Cairo University, Giza, Egypt

3 Faculty of Technology, Bielefeld University, Bielefeld, Germany

4 Centre for Biomedical Informatics, Harvard Medical School, USA

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BMC Bioinformatics 2012, 13(Suppl 17):S22  doi:10.1186/1471-2105-13-S17-S22

Published: 13 December 2012

Abstract

Background

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 webcite.