Bioinformatics clouds for big data manipulation

Handle URI:
http://hdl.handle.net/10754/325264
Title:
Bioinformatics clouds for big data manipulation
Authors:
Dai, Lin; Gao, Xin ( 0000-0002-7108-3574 ) ; Guo, Yan; Xiao, Jingfa; Zhang, Zhang
Abstract:
As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics.This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor. 2012 Dai et al.; licensee BioMed Central Ltd.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Dai L, Gao X, Guo Y, Xiao J, Zhang Z (2012) Bioinformatics clouds for big data manipulation. Biology Direct 7: 43. doi:10.1186/1745-6150-7-43.
Publisher:
BioMed Central
Journal:
Biology Direct
Issue Date:
28-Nov-2012
DOI:
10.1186/1745-6150-7-43
PubMed ID:
23190475
PubMed Central ID:
PMC3533974
Type:
Article
ISSN:
17456150
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorDai, Linen
dc.contributor.authorGao, Xinen
dc.contributor.authorGuo, Yanen
dc.contributor.authorXiao, Jingfaen
dc.contributor.authorZhang, Zhangen
dc.date.accessioned2014-08-27T09:43:16Z-
dc.date.available2014-08-27T09:43:16Z-
dc.date.issued2012-11-28en
dc.identifier.citationDai L, Gao X, Guo Y, Xiao J, Zhang Z (2012) Bioinformatics clouds for big data manipulation. Biology Direct 7: 43. doi:10.1186/1745-6150-7-43.en
dc.identifier.issn17456150en
dc.identifier.pmid23190475en
dc.identifier.doi10.1186/1745-6150-7-43en
dc.identifier.urihttp://hdl.handle.net/10754/325264en
dc.description.abstractAs advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics.This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor. 2012 Dai et al.; licensee BioMed Central Ltd.en
dc.language.isoenen
dc.publisherBioMed Centralen
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en
dc.subjectBig dataen
dc.subjectBioinformaticsen
dc.subjectCloud computingen
dc.subjectData analysisen
dc.subjectData storageen
dc.titleBioinformatics clouds for big data manipulationen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalBiology Directen
dc.identifier.pmcidPMC3533974en
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, No.7 Beitucheng West Road, Building G, Chaoyang District, Beijing, 100029, Chinaen
dc.contributor.institutionSchool of Computer Science and Technology, Beijing Institute of Technology, Beijing, 100081, Chinaen
dc.contributor.institutionCloud Development and Cloud Solution Integration, IBM China Systems and Technology Lab, IBM Co. Ltd, Beijing, 100193, Chinaen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorGao, Xinen

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