TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 17, No 3: June 2019

Parallel random projection using R high performance computing for planted motif search

Lala Septem Riza (Universitas Pendidikan Indonesia)
Tyas Farrah Dhiba (Universitas Pendidikan Indonesia)
Wawan Setiawan (Universitas Pendidikan Indonesia)
Topik Hidayat (Universitas Pendidikan Indonesia)
Mahmoud Fahsi (Djillali Liabes University)



Article Info

Publish Date
01 Jun 2019

Abstract

Motif discovery in DNA sequences is one of the most important issues in bioinformatics. Thus, algorithms for dealing with the problem accurately and quickly have always been the goal of research in bioinformatics. Therefore, this study is intended to modify the random projection algorithm to be implemented on R high performance computing (i.e., the R package pbdMPI). Some steps are needed to achieve this objective, ie preprocessing data, splitting data according to number of batches, modifying and implementing random projection in the pbdMPI package, and then aggregating the results. To validate the proposed approach, some experiments have been conducted. Several benchmarking data were used in this study by sensitivity analysis on number of cores and batches. Experimental results show that computational cost can be reduced, which is that the computation cost of 6 cores is faster around 34 times compared with the standalone mode. Thus, the proposed approach can be used for motif discovery effectively and efficiently.

Copyrights © 2019






Journal Info

Abbrev

TELKOMNIKA

Publisher

Subject

Computer Science & IT

Description

Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...