{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,6,2]],"date-time":"2022-06-02T02:40:30Z","timestamp":1654137630271},"reference-count":41,"publisher":"IGI Global","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,7,1]]},"abstract":"<p>Multiple sequence alignments with constraints are of priority concern in computational biology. Constrained sequence alignment incorporates the domain knowledge of biologists into sequence alignments such that the user-specified residues\/segments are aligned together according to the alignment results. A series of constrained multiple sequence alignment tools have been developed in relevant literatures in the recent decade. GPU-REMuSiC is the most advanced method with the regular expression constraints, in which graphics processing units (GPUs) with CUDA are used. GPU-REMuSiC can achieve a speedup ratio of 29x for overall computation time based on the experimental results. However, the execution environment of GPU-REMuSiC must be constructed; it is a threshold for biologists to set up it. Therefore, this work presents an intuitive friendly user interface of GPU-REMuSiC for the potential cloud server with GPUs, called Cloud GPU-REMuSiC. Implementing the user interface via a network allows us to transmit the input data to a remote server without a complex cumbersome setting in a local host. Finally, the alignment results can be obtained from a remote cloud server with GPUs. Cloud GPU-REMuSiC is highly promising as an online application that is accessible without time or location constraints.<\/p>","DOI":"10.4018\/jghpc.2013070105","type":"journal-article","created":{"date-parts":[[2013,11,25]],"date-time":"2013-11-25T19:04:07Z","timestamp":1385406247000},"page":"55-64","source":"Crossref","is-referenced-by-count":1,"title":["Multiple Sequence Alignments with Regular Expression Constraints on a Cloud Service System"],"prefix":"10.4018","volume":"5","author":[{"given":"Yu-Shiang","family":"Lin","sequence":"first","affiliation":[{"name":"National Tsing Hua University, Hsinchu, Taiwan"}]},{"given":"Chun-Yuan","family":"Lin","sequence":"additional","affiliation":[{"name":"Chang Gung University, Tao-Yuan, Taiwan"}]},{"given":"Hsiao-Chieh","family":"Chi","sequence":"additional","affiliation":[{"name":"National Tsing Hua University, Hsinchu, Taiwan"}]},{"given":"Yeh-Ching","family":"Chung","sequence":"additional","affiliation":[{"name":"National Tsing Hua University, Hsinchu, Taiwan"}]}],"member":"2432","reference":[{"key":"jghpc.2013070105-0","unstructured":"Armbrust, M, Fox, A., Griffith, R. Joseph, A. D., & Katz, R. (2009). Above the clouds: A Berkeley view of cloud computing. UC Berkeley Technical Repor."},{"key":"jghpc.2013070105-1","doi-asserted-by":"publisher","DOI":"10.1137\/0148063"},{"key":"jghpc.2013070105-2","doi-asserted-by":"publisher","DOI":"10.1142\/S0219720005000977"},{"key":"jghpc.2013070105-3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipl.2004.02.008"},{"key":"jghpc.2013070105-4","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkm275"},{"key":"jghpc.2013070105-5","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkm275"},{"key":"jghpc.2013070105-6","doi-asserted-by":"publisher","DOI":"10.1007\/11780441_35"},{"key":"jghpc.2013070105-7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipl.2007.04.007"},{"key":"jghpc.2013070105-8","doi-asserted-by":"publisher","DOI":"10.1109\/TC.1972.5009071"},{"key":"jghpc.2013070105-9","unstructured":"Galper, A. R., & Brutlag, D. L. (1990). Parallel similarity search and alignment with the dynamic programming method. Technique report, KSL-report (pp. 90-74)."},{"key":"jghpc.2013070105-10","doi-asserted-by":"crossref","unstructured":"He, D., & Arslan, A. N. (2005). A parallel algorithm for the constrained multiple sequence alignment problem. In Processing of BIBE (pp. 258\u2013262).","DOI":"10.1109\/BIBE.2006.253324"},{"key":"jghpc.2013070105-11","doi-asserted-by":"crossref","unstructured":"He, D., & Arslan, A. N. (2006). FastPCMSA: An improved parallel algorithm for the constrained multiple sequence alignment problem. In Processing of FCS (pp. 88\u201394).","DOI":"10.1109\/BIBE.2006.253324"},{"key":"jghpc.2013070105-12","unstructured":"He, D., & Arslan, A. N. (2006). Space-efficient parallel algorithms for the constrained multiple sequence alignment problem. In Processing of BIOCOMP (pp.10\u201316)."},{"issue":"4","key":"jghpc.2013070105-13","first-page":"701","article-title":"A fast algorithm for the constrained multiple sequence alignment problem.","volume":"17","author":"D.He","year":"2006","journal-title":"Acta Cybernetica"},{"key":"jghpc.2013070105-14","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2010.02.009"},{"key":"jghpc.2013070105-15","doi-asserted-by":"publisher","DOI":"10.1109\/71.494636"},{"key":"jghpc.2013070105-16","doi-asserted-by":"crossref","unstructured":"Ligowski, L., & Rudnicki, W. (2009). An efficient implementation of Smith-Waterman algorithm on GPU using CUDA, for massively parallel scanning of sequence databases. In Processing of HiCOMB.","DOI":"10.1109\/IPDPS.2009.5160931"},{"key":"jghpc.2013070105-17","unstructured":"Lin, C. Y., Lin, Y. S., Zhou, J., & Tang, C. Y. (2011). GPU-REMuSiC: Efficient constrained multiple sequence alignment algorithm on graphics processing units. In Proceeding of CTHPC."},{"key":"jghpc.2013070105-18","doi-asserted-by":"publisher","DOI":"10.1007\/11945918_37"},{"key":"jghpc.2013070105-19","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2007.1069"},{"key":"jghpc.2013070105-20","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2011.33"},{"key":"jghpc.2013070105-21","doi-asserted-by":"publisher","DOI":"10.1186\/1756-0500-2-73"},{"key":"jghpc.2013070105-22","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2009.10.009"},{"key":"jghpc.2013070105-23","unstructured":"Liu, Y., Schmidt, B., & Maskell, D. L. (2009). MSA-CUDA: multiple sequence alignment on graphics processing units with CUDA. In Processing of ASAP (pp. 121\u2013128)."},{"key":"jghpc.2013070105-24","doi-asserted-by":"publisher","DOI":"10.1186\/1756-0500-3-93"},{"key":"jghpc.2013070105-25","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bth468"},{"key":"jghpc.2013070105-26","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-9-S2-S10"},{"key":"jghpc.2013070105-27","doi-asserted-by":"publisher","DOI":"10.1089\/cmb.1996.3.563"},{"key":"jghpc.2013070105-28","doi-asserted-by":"publisher","DOI":"10.1016\/0022-2836(70)90057-4"},{"key":"jghpc.2013070105-29","doi-asserted-by":"publisher","DOI":"10.1145\/1365490.1365500"},{"key":"jghpc.2013070105-30","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2004.86"},{"key":"jghpc.2013070105-31","doi-asserted-by":"crossref","unstructured":"Sandes, F. D. O., & Melo, A. C. M. A. D. (2010). CUDAlign: Using GPU to accelerate the comparison of megabase genomic sequences. In Processing of PPOPP (pp. 137\u2013146).","DOI":"10.1145\/1837853.1693473"},{"key":"jghpc.2013070105-32","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-8-474"},{"key":"jghpc.2013070105-33","doi-asserted-by":"publisher","DOI":"10.1016\/0022-2836(81)90087-5"},{"key":"jghpc.2013070105-34","doi-asserted-by":"crossref","unstructured":"Striemer, G. M., & Akoglu, A. (2009). Sequence alignment with GPU: performance and design challenges. In Processing of IPDPS (pp.1\u201310).","DOI":"10.1109\/IPDPS.2009.5161066"},{"key":"jghpc.2013070105-35","doi-asserted-by":"publisher","DOI":"10.1142\/S0219720003000095"},{"key":"jghpc.2013070105-36","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/22.22.4673"},{"key":"jghpc.2013070105-37","doi-asserted-by":"publisher","DOI":"10.1016\/j.parco.2009.05.002"},{"key":"jghpc.2013070105-38","unstructured":"Tsai, H., Lin, C. Y., Chung, Y.-C., & Tang, C. Y. (2006). An efficient parallel algorithm for constraint multiple sequence alignment. In Processing of ICS (pp. 1261\u20131266)."},{"key":"jghpc.2013070105-39","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipl.2003.07.001"},{"key":"jghpc.2013070105-40","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bth220"}],"container-title":["International Journal of Grid and High Performance Computing"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=95118","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,2]],"date-time":"2022-06-02T02:22:32Z","timestamp":1654136552000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/jghpc.2013070105"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2013,7,1]]},"references-count":41,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2013,7]]}},"URL":"https:\/\/doi.org\/10.4018\/jghpc.2013070105","relation":{},"ISSN":["1938-0259","1938-0267"],"issn-type":[{"value":"1938-0259","type":"print"},{"value":"1938-0267","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,7,1]]}}}