Development of MapReduce and MPI programs for motif search

Mejdl Safran, Saad Al-Qahtani, Michelle Zhu, Dunren Che

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

As one of the important problems in molecular biology, motif search is computationally expensive, especially when the size of DNA sequences is large. Extended from a graduate course project in parallel and distributed computing (PDC), this paper investigates two different programming frameworks, namely MapReduce and MPI on motif finding. We implemented a serial algorithm, a MapReduce based algorithm, and a MPI program to calculate the best motif in given DNA sequences. The experimental results demonstrate that our MPI program outperformed both the MapReduce-based algorithm and the serial program with superior efficiency.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages500-501
Number of pages2
ISBN (Electronic)9781467365987
DOIs
StatePublished - 26 Oct 2015
EventIEEE International Conference on Cluster Computing, CLUSTER 2015 - Chicago, United States
Duration: 8 Sep 201511 Sep 2015

Publication series

NameProceedings - IEEE International Conference on Cluster Computing, ICCC
Volume2015-October
ISSN (Print)1552-5244

Other

OtherIEEE International Conference on Cluster Computing, CLUSTER 2015
CountryUnited States
CityChicago
Period8/09/1511/09/15

Fingerprint

DNA sequences
Molecular biology
Distributed computer systems
Parallel processing systems

Keywords

  • Algorithm
  • MPI
  • MapReduce
  • Motif
  • Parallel processing

Cite this

Safran, M., Al-Qahtani, S., Zhu, M., & Che, D. (2015). Development of MapReduce and MPI programs for motif search. In Proceedings - 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015 (pp. 500-501). [7307629] (Proceedings - IEEE International Conference on Cluster Computing, ICCC; Vol. 2015-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CLUSTER.2015.82
Safran, Mejdl ; Al-Qahtani, Saad ; Zhu, Michelle ; Che, Dunren. / Development of MapReduce and MPI programs for motif search. Proceedings - 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 500-501 (Proceedings - IEEE International Conference on Cluster Computing, ICCC).
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Safran, M, Al-Qahtani, S, Zhu, M & Che, D 2015, Development of MapReduce and MPI programs for motif search. in Proceedings - 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015., 7307629, Proceedings - IEEE International Conference on Cluster Computing, ICCC, vol. 2015-October, Institute of Electrical and Electronics Engineers Inc., pp. 500-501, IEEE International Conference on Cluster Computing, CLUSTER 2015, Chicago, United States, 8/09/15. https://doi.org/10.1109/CLUSTER.2015.82

Development of MapReduce and MPI programs for motif search. / Safran, Mejdl; Al-Qahtani, Saad; Zhu, Michelle; Che, Dunren.

Proceedings - 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 500-501 7307629 (Proceedings - IEEE International Conference on Cluster Computing, ICCC; Vol. 2015-October).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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N2 - As one of the important problems in molecular biology, motif search is computationally expensive, especially when the size of DNA sequences is large. Extended from a graduate course project in parallel and distributed computing (PDC), this paper investigates two different programming frameworks, namely MapReduce and MPI on motif finding. We implemented a serial algorithm, a MapReduce based algorithm, and a MPI program to calculate the best motif in given DNA sequences. The experimental results demonstrate that our MPI program outperformed both the MapReduce-based algorithm and the serial program with superior efficiency.

AB - As one of the important problems in molecular biology, motif search is computationally expensive, especially when the size of DNA sequences is large. Extended from a graduate course project in parallel and distributed computing (PDC), this paper investigates two different programming frameworks, namely MapReduce and MPI on motif finding. We implemented a serial algorithm, a MapReduce based algorithm, and a MPI program to calculate the best motif in given DNA sequences. The experimental results demonstrate that our MPI program outperformed both the MapReduce-based algorithm and the serial program with superior efficiency.

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Safran M, Al-Qahtani S, Zhu M, Che D. Development of MapReduce and MPI programs for motif search. In Proceedings - 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 500-501. 7307629. (Proceedings - IEEE International Conference on Cluster Computing, ICCC). https://doi.org/10.1109/CLUSTER.2015.82