Review on Genome Sequence using Hadoop and MapReduce

Anushree , Rio G. L. D'Souza

Genome Sequence, DNA Sequence, Hadoop, Mapreduce.

Next generation sequencing has led to the generation of billions of sequence data, making it increasingly infeasible for sequence alignment to be performed on standalone machines. The Digital data can be stored in the form of genome sequence, which requires techniques to synthesise and sequence into the DNA sequences. This paper reviews about taking a dataset of DNA sequencing as an input and split them across the cluster machine by applying MapReduce implementation of Hadoop to make the search efficient for large scale genome sequencing applications.

Published Paper   E-Certificate

"Review on Genome Sequence using Hadoop and MapReduce", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.3, Issue 11, page no.214 - 218, November-2018, Available :https://ijsdr.org/papers/IJSDR1811037.pdf

Volume 3 Issue 11, November-2018

Pages : 214 - 218

Paper Reg. ID: IJSDR_180797

Published Paper Id: IJSDR1811037

Downloads: 000347166

Research Area: Engineering

Country: Mangaluru, Karnataka, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR1811037

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR1811037

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition