Cloud Computing for Comparative Genomics with Windows Azure Platform

Insik Kim; Jae-Yoon Jung; Todd F. DeLuca; Tristan H. Nelson; Dennis P. Wall

doi:10.4137/EBO.S9946

Evolutionary Bioinformatics (Jan 2012)

Cloud Computing for Comparative Genomics with Windows Azure Platform

Insik Kim,
Jae-Yoon Jung,
Todd F. DeLuca,
Tristan H. Nelson,
Dennis P. Wall

Affiliations

Insik Kim: School of Electrical and Computer Engineering, Ulsan National Institute of Technology, Ulsan, Korea.
Jae-Yoon Jung: Center for Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Todd F. DeLuca: Center for Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Tristan H. Nelson: Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Dennis P. Wall: Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA.

DOI: https://doi.org/10.4137/EBO.S9946
Journal volume & issue: Vol. 8

Abstract

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Cloud computing services have emerged as a cost-effective alternative for cluster systems as the number of genomes and required computation power to analyze them increased in recent years. Here we introduce the Microsoft Azure platform with detailed execution steps and a cost comparison with Amazon Web Services.

Published in Evolutionary Bioinformatics

ISSN: 1176-9343 (Online)
Publisher: SAGE Publishing
Country of publisher: United States
LCC subjects: Science: Biology (General): Evolution
Website: https://journals.sagepub.com/home/evb

About the journal