Bioinformatics clouds for big data manipulation

<p<Abstract</p< <p<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...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Dai Lin [verfasserIn] Gao Xin [verfasserIn] Guo Yan [verfasserIn] Xiao Jingfa [verfasserIn] Zhang Zhang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2012

Schlagwörter:	Cloud computing Bioinformatics Big data Data storage Data analysis

Übergeordnetes Werk:	In: Biology Direct - BMC, 2006, 7(2012), 1, p 43
Übergeordnetes Werk:	volume:7 ; year:2012 ; number:1, p 43

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1186/1745-6150-7-43

Katalog-ID:	DOAJ031925650

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topic	misc QH301-705.5 misc Cloud computing misc Bioinformatics misc Big data misc Data storage misc Data analysis misc Biology (General)
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title	Bioinformatics clouds for big data manipulation
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abstract	<p<Abstract</p< <p<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.</p< <p<Reviewers</p< <p<This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.</p<
abstractGer	<p<Abstract</p< <p<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.</p< <p<Reviewers</p< <p<This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.</p<
abstract_unstemmed	<p<Abstract</p< <p<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.</p< <p<Reviewers</p< <p<This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.</p<
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