Applications of grid computing in genetics and proteomics

Authors:
Jorge Andrade;Malin Andersen;Lisa Berglund;Jacob Odeberg
Affiliations:
Department of Biotechnology, Royal Institute of Technology (KTH), AlbaNova University Center, Stockholm, Sweden;Dept. of Biotechn., Royal Inst. of Techn. (KTH), AlbaNova Univ. Center, Stockholm, Sweden and Dept. of Medicine, Atherosclerosis Research Unit, King Gustaf V Res. Inst., Karolinska Institutet, Kar ...;Department of Biotechnology, Royal Institute of Technology (KTH), AlbaNova University Center, Stockholm, Sweden;Dept. of Biotechnology, Royal Inst. of Techn. (KTH), AlbaNova Univ. Center, Stockholm, Sweden and Dept. of Medicine, Atherosclerosis Research Unit, King Gustaf V Res. Inst., Karolinska Institutet, ...
Venue:
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
Year:
2006

Citing 5
Cited 1

The Anatomy of the Grid: Enabling Scalable Virtual Organizations

International Journal of High Performance Computing Applications
Mechanisms for increasing the usability of grid security

International Journal of Human-Computer Studies - Special isssue: HCI research in privacy and security is critical now
An Interoperable, Standards-Based Grid Resource Broker and Job Submission Service

E-SCIENCE '05 Proceedings of the First International Conference on e-Science and Grid Computing
Advanced resource connector middleware for lightweight computational Grids

Future Generation Computer Systems - Special section: Information engineering and enterprise architecture in distributed computing environments
Grid resource brokering algorithms enabling advance reservations and resource selection based on performance predictions

Future Generation Computer Systems

A framework for readapting and running bioinformatics applications in the cloud

Proceedings of the 2012 ACM Research in Applied Computation Symposium

Quantified Score

Hi-index	0.00

Visualization

Abstract

The potential for Grid technologies in applied bioinformatics is largely unexplored. We have developed a model for solving computationally demanding bioinformatics tasks in distributed Grid environments, designed to ease the usability for scientists unfamiliar with Grid computing. With a script-based implementation that uses a strategy of temporary installations of databases and existing executables on remote nodes at submission, we propose a generic solution that do not rely on predefined Grid runtime environments and that can easily be adapted to other bioinformatics tasks suitable for parallelization. This implementation has been successfully applied to whole proteome sequence similarity analyses and to genome-wide genotype simulations, where computation time was reduced from years to weeks. We conclude that computational Grid technology is a useful resource for solving high compute tasks in genetics and proteomics using existing algorithms.