Cloud Computing for Comparative Genomics with Windows Azure Platform

Overview

Journal Evol Bioinform Online

Publisher Sage Publications

Specialty Biology

Date 2012 Oct 4

PMID 23032609

Citations 3

Authors

Insik Kim

Jae-Yoon Jung

Todd F DeLuca

Tristan H Nelson

Dennis P Wall

Affiliations

Soon will be listed here.

Abstract

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.

Citing Articles

Enabling large-scale biomedical analysis in the cloud.

Lin Y, Yu C, Lin Y Biomed Res Int. 2013; 2013:185679.

PMID: 24288665 PMC: 3832998. DOI: 10.1155/2013/185679.

Translational biomedical informatics in the cloud: present and future.

Chen J, Qian F, Yan W, Shen B Biomed Res Int. 2013; 2013:658925.

PMID: 23586054 PMC: 3613081. DOI: 10.1155/2013/658925.

Now and next-generation sequencing techniques: future of sequence analysis using cloud computing.

Thakur R, Bandopadhyay R, Chaudhary B, Chatterjee S Front Genet. 2012; 3:280.

PMID: 23248640 PMC: 3518790. DOI: 10.3389/fgene.2012.00280.

References

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