BLAST Using Big Data Technologies: A Survey

被引：0
|
作者：
Gaikwad, Mayur [1 ]
Ahirrao, Swati [1 ]
机构：
[1] Symbiosis Inst Technol, Dept Comp Sci, Pune, Maharashtra, India
来源：
2018 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA) | 2018年
关键词：
BLAST; Big Data; Hadoop; map reduce; genome sequence; ALIGNMENT; SEQUENCE; SEARCH; SIMILARITY; TOOLKIT;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
With advent of Next Generation Sequencing, large amount of sequence data is generated. This sequence data is analyzed for different purposes like its function, features and mutations. Algorithms like Needleman-Wunsch, Smith-Waterman, and BLAST help to find homologous sequences, but they require huge computation time for processing large sequences. Therefore, Big Data technologies are used with sequencing algorithms to scale down time, space and CPU consumption. Large sequences also require more time to transfer from one machine to another, and also for analysis. In this paper, the survey of existing work related on BLAST with MapReduce framework is discussed and the case for real-time genome sequence analysis is presented.
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页数：5
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