Abstract

Multiple sequence alignment (MSA) methods are essential in biological analysis. Several MSA algorithms have been proposed in recent years. The quality of the results produced by those methods is reasonable, but there is no single method that consistently outperforms others. Additionally, the increasing number of sequences in the biological databases is perceived as one of the upcoming challenges for alignment methods in the nearest future. The lack of performance concerns not only the alignment problems, but may be observed in many areas of biologically related research.To overcome this problem in the field of pairwise alignment, several GPU (Graphics Processing Unit) computing approaches have been proposed lately. These solutions show a great potential of GPU platform. Therefore, our main idea was to design and implement an MSA method which can take advantage of modern graphics cards. Our solution is based on T-Coffee–well known for its high accuracy MSA algorithm. Its computational time, however, is often unacceptable. Performed tests show that our method, named G-MSA, is highly efficient achieving up to 193-fold speedup on a single GPU while the quality of its results remains very good. Due to effective memory usage the method can perform alignment for huge sets of sequences that previously could only be aligned on computer clusters. Moreover, multiple GPUs support with load balancing makes the application very scalable.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.