Improving Performance of Multiple Sequence Alignment Analysis in Multi-Client Environments
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
A component-based implementation of multiple sequence alignment
Proceedings of the 2003 ACM symposium on Applied computing
Parallel Multiple Sequence Alignment with Dynamic Scheduling
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume I - Volume 01
Multiple Sequence Alignment on an FPGA
ICPADS '05 Proceedings of the 11th International Conference on Parallel and Distributed Systems - Workshops - Volume 02
Parallel CLUSTAL W for PC clusters
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartII
Multiple Sequence Alignment with Evolutionary-Progressive Method
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Pairwise Distance Matrix Computation for Multiple Sequence Alignment on the Cell Broadband Engine
ICCS '09 Proceedings of the 9th International Conference on Computational Science: Part I
Experiences with parallelizing a bio-informatics program on the cell BE
HiPEAC'08 Proceedings of the 3rd international conference on High performance embedded architectures and compilers
The Journal of Supercomputing
Hi-index | 0.00 |
ClustalW is the most widely used tool for aligning multiple protein or nucleotide sequences. The alignment is achieved via three stages: pairwise alignment, guide tree generation and progressive alignment. This paper analyzes and enhances a multithreaded implementation of ClustalW called ClustalW-SMP for higher throughput. Our goal is to maximize the degree of parallelism on multithreading ClustalW called MultiThreading-ClustalW (MT-ClustalW). As a result, bioinformatics laboratories are able to use this MTClustalW with much less energy consumption on multicore and SMP (Symmetric MultiProcessor) machines than that of PC clusters. The experiment results show that the MT-ClustalW framework can achieve a considerable speedup over the sequential ClustalW and original multithreaded ClustalW-SMP implementations.