Table of Contents
ISRN Biomathematics
Volume 2013 (2013), Article ID 615630, 14 pages
http://dx.doi.org/10.1155/2013/615630
Review Article

An Overview of Multiple Sequence Alignments and Cloud Computing in Bioinformatics

1Department of Biological Sciences, Cork Institute of Technology, Rossa Avenue, Bishopstown, Cork, Ireland
2Department of Computing, Cork Institute of Technology, Rossa Avenue, Bishopstown, Cork, Ireland

Received 24 May 2013; Accepted 23 June 2013

Academic Editors: M. Glavinovic and X.-Y. Lou

Copyright © 2013 Jurate Daugelaite et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Multiple sequence alignment (MSA) of DNA, RNA, and protein sequences is one of the most essential techniques in the fields of molecular biology, computational biology, and bioinformatics. Next-generation sequencing technologies are changing the biology landscape, flooding the databases with massive amounts of raw sequence data. MSA of ever-increasing sequence data sets is becoming a significant bottleneck. In order to realise the promise of MSA for large-scale sequence data sets, it is necessary for existing MSA algorithms to be run in a parallelised fashion with the sequence data distributed over a computing cluster or server farm. Combining MSA algorithms with cloud computing technologies is therefore likely to improve the speed, quality, and capability for MSA to handle large numbers of sequences. In this review, multiple sequence alignments are discussed, with a specific focus on the ClustalW and Clustal Omega algorithms. Cloud computing technologies and concepts are outlined, and the next generation of cloud base MSA algorithms is introduced.