An Overview of Multiple Sequence Alignments and Cloud Computing in Bioinformatics. (14th August 2013)

• Record Type: Journal Article
• Authors: Daugelaite, Jurate; O' Driscoll, Aisling; Sleator, Roy D.
• Other Names: Glavinovic M. Academic Editor.; Lou X.-Y. Academic Editor.
• Is Part Of: ISRN biomathematics. Volume 2013(2013)
• Publication Date: 2013-08-14
• Subjects: Biomathematics -- Periodicals; Models, Biological; Biometry; Biomathematics; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 570.151
• DOI: 10.1155/2013/615630
• Languages: English
• ISSNs: 2090-7702

Abstract

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.