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2018 | OriginalPaper | Chapter

Parka: A Parallel Implementation of BLAST with MapReduce

Authors : Li Zhang, Bing Tang

Published in: Advances in Intelligent Systems and Interactive Applications

Publisher: Springer International Publishing

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Abstract

Bioinformatics applications have become more data-intensive and compute-intensive, which requires an effective method to implement parallel computing and get a high-throughput. Although there exists some tools to realize parallelization of BLAST, but most of them depend on complex platforms or software. A parallel BLAST is implemented using Spark, which is called Parka. The parallel execution time and speedup of Parka are evaluated in a cluster environment. Then, it is compared with Hadoop-based parallelization method. Results show that it is a scalable and effective parallelization approach for sequence alignment.

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Metadata
Title
Parka: A Parallel Implementation of BLAST with MapReduce
Authors
Li Zhang
Bing Tang
Copyright Year
2018
Book
Advances in Intelligent Systems and Interactive Applications

Print ISBN: 978-3-319-69095-7

Electronic ISBN: 978-3-319-69096-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-69096-4_26

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