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Open AccessJournal ArticleDOI

'Big data', Hadoop and cloud computing in genomics

TLDR
An overview of cloud computing and big data technologies, and how such expertise can be used to deal with biology's big data sets is discussed, together with an overview of the current usage of Hadoop within the bioinformatics community.
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This article is published in Journal of Biomedical Informatics.The article was published on 2013-10-01 and is currently open access. It has received 403 citations till now. The article focuses on the topics: Data-intensive computing & Big data.

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Citations
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Journal ArticleDOI

Securing Big Data Provenance for Auditors: The Big Data Provenance Black Box as Reliable Evidence

TL;DR: An issue regarding reliable audit evidence derived from Big Data—that of secure data provenance—is highlighted, which needs to be securely maintained so that it cannot be thwarted.
Book ChapterDOI

Cloud-Based Big Data Analytics—A Survey of Current Research and Future Directions

TL;DR: The existing research, challenges, open issues, and future research direction for cloud-based analytics are explored, with a view to practical applications of this synergistic model can be popularly used.
Journal ArticleDOI

HBLAST: Parallelised sequence similarity – A Hadoop MapReducable basic local alignment search tool

TL;DR: HBlast presents improved scalability over existing solutions and well balanced computational work load while keeping database segmentation and recompilation to a minimum, and Enhanced BLAST search performance on cheap memory constrained hardware has significant implications for in field clinical diagnostic testing.
Journal ArticleDOI

Tackling Epilepsy With High-definition Precision Medicine: A Review.

TL;DR: A panoramic approach to treatment encompassing both molecular diagnostic techniques and amelioration of network function by addressing factors beyond seizure reduction may be considered as part of a high-definition approach to tackling epilepsy.
Journal ArticleDOI

Sharing big biomedical data

TL;DR: This paper provides a framework for developing practical and reasonable data sharing policies that incorporate the sociological, financial, technical and scientific requirements of a sustainable Big Data dependent scientific community.
References
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Journal ArticleDOI

The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data

TL;DR: The GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
Journal ArticleDOI

Cramming More Components Onto Integrated Circuits

TL;DR: Integrated circuits will lead to such wonders as home computers or at least terminals connected to a central computer, automatic controls for automobiles, and personal portable communications equipment as mentioned in this paper. But the biggest potential lies in the production of large systems.
Journal Article

Cramming More Components onto Integrated Circuits

Gordon E. Moore
- 01 Jan 1965 - 
TL;DR: Integrated circuits will lead to such wonders as home computers or at least terminals connected to a central computer, automatic controls for automobiles, and personal portable communications equipment as discussed by the authors. But the biggest potential lies in the production of large systems.
Book

Big data: The next frontier for innovation, competition, and productivity

James Manyika
TL;DR: The amount of data in the authors' world has been exploding, and analyzing large data sets will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey.
Journal ArticleDOI

Galaxy: A platform for interactive large-scale genome analysis

TL;DR: An interactive system, Galaxy, that combines the power of existing genome annotation databases with a simple Web portal to enable users to search remote resources, combine data from independent queries, and visualize the results.
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