'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.read more
Citations
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SWARAM: Portable Energy and Cost Efficient Embedded System for Genomic Processing
TL;DR: This work presents a meta-modelling architecture suitable for embedded embedded computing systems with real-time interrupts and provides a simple, scalable, and scalable architecture for smart grids.
Journal ArticleDOI
Application of Genetic Algorithms for the Estimation of Hydraulic Conductivity
TL;DR: In this article, an alternative methodology based on genetic algorithms is presented for the determination of the basic parameters of Biot consolidation model, which has been demonstrated that GA is a highly effective tool enabling automatic calibration based on simple rules.
Data Aggregation in Healthcare Applications and BIGDATA set in a FOG based Cloud System
TL;DR: This chapter presents the problems of currently available simple cloud systems for day-to-day applications and also proposes a better and new network and system architecture that is the future of could computing – commonly known as the Fog networks.
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Information technology for clinical, translational and comparative effectiveness research. Findings from the section clinical research informatics.
Christel Daniel,R. Choquet +1 more
TL;DR: A synopsis of the articles selected for the IMIA Yearbook 2015, from which a synthetic overview of current and future activities in the field is derived, to summarize excellent current research with application in the health domain and clinical care.
References
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The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
Aaron McKenna,Matthew Hanna,Eric Banks,Andrey Sivachenko,Kristian Cibulskis,Andrew Kernytsky,Kiran V. Garimella,David Altshuler,Stacey Gabriel,Mark J. Daly,Mark A. DePristo +10 more
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.
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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
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
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.
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Galaxy: A platform for interactive large-scale genome analysis
Belinda Giardine,Cathy Riemer,Ross C. Hardison,Richard Burhans,Laura Elnitski,Prachi Shah,Prachi Shah,Yi Zhang,Daniel Blankenberg,Istvan Albert,James Taylor,Webb Miller,W. James Kent,Anton Nekrutenko +13 more
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.