The University of Southampton
University of Southampton Institutional Repository

BioSimGrid: grid-enabled biomolecular simulation data storage and analysis

Ng, Muan Hong, Johnston, Steven, Wu, Bing, Murdock, Stuart E., Tai, Kaihsu, Fangohr, Hans, Cox, Simon J., Essex, Jonathan W., Sansom, Mark S.P. and Jeffreys, Paul (2006) BioSimGrid: grid-enabled biomolecular simulation data storage and analysis Future Generation Computer Systems, 6, (22), pp. 657-664. (doi:10.1016/j.future.2005.10.005).

Record type: Article

Abstract

In computational biomolecular research, large amounts of simulation data are generated to capture the motion of proteins. These massive simulation data can be analysed in a number of ways to reveal the biochemical properties of the proteins. However, the legacy way of storing these data (usually in the laboratory where the simulations have been run) often hinders a wider sharing and easier cross-comparison of simulation results. The data is commonly encoded in a way specific to the simulation package that produced the data and can only be analysed with tools developed specifically for that simulation package. The BioSimGrid platform seeks to provide a solution to these challenges by exploiting the potential of the Grid in facilitating data sharing. By using BioSimGrid either in a scripting or web environment, users can deposit their data and reuse it for analysis. BioSimGrid tools manage the multiple storage locations transparently to the users and provide a set of retrieval and analysis tools for processing the data in a convenient and efficient manner. This paper details the usage and implementation of BioSimGrid using a combination of commercial databases, the Storage Resource Broker and Python scripts, gluing the building blocks together. It introduces a case study of how BioSimGrid can be used for better storage, retrieval and analysis of biomolecular simulation data.

PDF Ng_06pp.pdf - Accepted Manuscript
Download (1MB)

More information

Submitted date: 15 August 2005
Published date: May 2006
Keywords: biomolecular simulation, database, grid computing, storage resource broker, python

Identifiers

Local EPrints ID: 65004
URI: http://eprints.soton.ac.uk/id/eprint/65004
PURE UUID: 0d4490b2-91b2-408c-8be2-839823bcb047
ORCID for Steven Johnston: ORCID iD orcid.org/0000-0003-3864-7072
ORCID for Jonathan W. Essex: ORCID iD orcid.org/0000-0003-2639-2746

Catalogue record

Date deposited: 27 Jan 2009
Last modified: 17 Jul 2017 14:10

Export record

Altmetrics

Contributors

Author: Muan Hong Ng
Author: Steven Johnston ORCID iD
Author: Bing Wu
Author: Stuart E. Murdock
Author: Kaihsu Tai
Author: Hans Fangohr
Author: Simon J. Cox
Author: Mark S.P. Sansom
Author: Paul Jeffreys

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×