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The Widening Gulf between Genomics Data Generation and Consumption: A Practical Guide to Big Data Transfer Technology
Author(s) -
F. Alex Feltus,
Joseph R. Breen,
Juan Deng,
Ryan Izard,
Christopher A. Konger,
W.B. Ligon,
Don Preuss,
KuangChing Wang
Publication year - 2015
Publication title -
bioinformatics and biology insights
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 23
ISSN - 1177-9322
DOI - 10.4137/bbi.s28988
Subject(s) - data science , big data , computer science , snapshot (computer storage) , genomics , data mining , genome , database , biology , gene , biochemistry
In the last decade, high-throughput DNA sequencing has become a disruptive technology and pushed the life sciences into a distributed ecosystem of sequence data producers and consumers. Given the power of genomics and declining sequencing costs, biology is an emerging "Big Data" discipline that will soon enter the exabyte data range when all subdisciplines are combined. These datasets must be transferred across commercial and research networks in creative ways since sending data without thought can have serious consequences on data processing time frames. Thus, it is imperative that biologists, bioinformaticians, and information technology engineers recalibrate data processing paradigms to fit this emerging reality. This review attempts to provide a snapshot of Big Data transfer across networks, which is often overlooked by many biologists. Specifically, we discuss four key areas: 1) data transfer networks, protocols, and applications; 2) data transfer security including encryption, access, firewalls, and the Science DMZ; 3) data flow control with software-defined networking; and 4) data storage, staging, archiving and access. A primary intention of this article is to orient the biologist in key aspects of the data transfer process in order to frame their genomics-oriented needs to enterprise IT professionals.

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