Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Journal of Integrative Bioinformatics

Editor-in-Chief: Schreiber, Falk / Hofestädt, Ralf

Managing Editor: Sommer, Björn

Ed. by Baumbach, Jan / Chen, Ming / Orlov, Yuriy / Allmer, Jens

Editorial Board: Giorgetti, Alejandro / Harrison, Andrew / Kochetov, Aleksey / Krüger, Jens / Ma, Qi / Matsuno, Hiroshi / Mitra, Chanchal K. / Pauling, Josch K. / Rawlings, Chris / Fdez-Riverola, Florentino / Romano, Paolo / Röttger, Richard / Shoshi, Alban / Soares, Siomar de Castro / Taubert, Jan / Tauch, Andreas / Yousef, Malik / Weise, Stephan / Hassani-Pak, Keywan


CiteScore 2018: 0.90

SCImago Journal Rank (SJR) 2018: 0.315

Open Access
Online
ISSN
1613-4516
See all formats and pricing
More options …
Volume 9, Issue 2

Issues

Microbase2.0: A Generic Framework for Computationally Intensive Bioinformatics Workflows in the Cloud

Keith Flanagan / Sirintra Nakjang
  • School of Computing Science United Kingdom of Great Britain and Northern Ireland
  • Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle upon Tyne, NE7 4RU, United Kingdom of Great Britain and Northern Ireland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jennifer Hallinan / Colin Harwood
  • Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle upon Tyne, NE7 4RU, United Kingdom of Great Britain and Northern Ireland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Robert P. Hirt
  • Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle upon Tyne, NE7 4RU, United Kingdom of Great Britain and Northern Ireland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Matthew R. Pocock / Anil Wipat
Published Online: 2016-10-18 | DOI: https://doi.org/10.1515/jib-2012-212

Summary

As bioinformatics datasets grow ever larger, and analyses become increasingly complex, there is a need for data handling infrastructures to keep pace with developing technology. One solution is to apply Grid and Cloud technologies to address the computational requirements of analysing high throughput datasets. We present an approach for writing new, or wrapping existing applications, and a reference implementation of a framework, Microbase2.0, for executing those applications using Grid and Cloud technologies. We used Microbase2.0 to develop an automated Cloud-based bioinformatics workflow executing simultaneously on two different Amazon EC2 data centres and the Newcastle University Condor Grid. Several CPU years’ worth of computational work was performed by this system in less than two months. The workflow produced a detailed dataset characterising the cellular localisation of 3,021,490 proteins from 867 taxa, including bacteria, archaea and unicellular eukaryotes. Microbase2.0 is freely available from http://www.microbase.org.uk/.

About the article

Published Online: 2016-10-18

Published in Print: 2012-06-01


Citation Information: Journal of Integrative Bioinformatics, Volume 9, Issue 2, Pages 101–112, ISSN (Online) 1613-4516, DOI: https://doi.org/10.1515/jib-2012-212.

Export Citation

© 2012 The Author(s). Published by Journal of Integrative Bioinformatics.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

Comments (0)

Please log in or register to comment.
Log in