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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.
About
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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The rise of big data on cloud computing

TL;DR: The definition, characteristics, and classification of big data along with some discussions on cloud computing are introduced, and research challenges are investigated, with focus on scalability, availability, data integrity, data transformation, data quality, data heterogeneity, privacy, legal and regulatory issues, and governance.
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MeDShare: Trust-Less Medical Data Sharing Among Cloud Service Providers via Blockchain

TL;DR: The proposed MeDShare system is blockchain-based and provides data provenance, auditing, and control for shared medical data in cloud repositories among big data entities and employs smart contracts and an access control mechanism to effectively track the behavior of the data.
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Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science

TL;DR: In this article, the authors look at how data-driven techniques are playing a big role in deciphering processing-structure-property-performance relationships in materials, with illustrative examples of both forward models (property prediction) and inverse models (materials discovery).
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Industry 4.0 and Health: Internet of Things, Big Data, and Cloud Computing for Healthcare 4.0

TL;DR: By selectively analyzing the literature, this paper systematically survey how the adoption of the above-mentioned Industry 4.0 technologies (and their integration) applied to the health domain is changing the way to provide traditional services and products.
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Big Data: Survey, Technologies, Opportunities, and Challenges

TL;DR: This study comprehensively surveys and classifies the various attributes of Big data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security, and proposes a data life cycle that uses the technologies and terminologies of Big Data.
References
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Journal ArticleDOI

SOAP3: ultra-fast GPU-based parallel alignment tool for short reads.

TL;DR: SOAP3 is the first short read alignment tool that leverages the multi-processors in a graphic processing unit (GPU) to achieve a drastic improvement in speed and aligns slightly more reads than BWA and Bowtie.
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Gpu-blast

TL;DR: GPU-BLAST is developed, an accelerated version of the popular NCBI-BLast, based on the source code ofNCBI- BLAST, thus maintaining the same input and output interface while producing identical results.
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Survey of MapReduce frame operation in bioinformatics

TL;DR: This article presents MapReduce frame-based applications that can be employed in the next-generation sequencing and other biological domains and discusses the challenges faced by this field as well as the future works on parallel computing in bioinformatics.
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A Dynamical-Systems View of Stem Cell Biology

TL;DR: In this article, the authors review relevant dynamical-systems approaches to describe the state transition between stem and differentiated cells, with an emphasis on fluctuating and oscillatory gene expression levels, as these represent the specific properties of stem cells.
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PeakRanger: A cloud-enabled peak caller for ChIP-seq data

TL;DR: PeakRanger is introduced, a peak caller software package that works equally well on punctate and broad sites, can resolve closely-spaced peaks, has excellent performance, and is easily customized.
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