'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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The role of Information and Communication Technologies in healthcare: taxonomies, perspectives, and challenges
TL;DR: An up-to-date picture of the novel healthcare applications enabled by the ICTs advancements, with a focus on their specific hottest research challenges is provided, to help the interested readership not to lose orientation in the complex landscapes possibly generated when advanced ICTS are adopted in application scenarios dictated by the critical healthcare domain.
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Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline.
Jeffrey G. Reid,Andrew Carroll,Narayanan Veeraraghavan,Mahmoud Dahdouli,Andreas Sundquist,Adam C. English,Matthew N. Bainbridge,Simon D. M. White,William J Salerno,Christian J. Buhay,Fuli Yu,Donna M. Muzny,Richard Daly,Geoff Duyk,Richard A. Gibbs,Eric Boerwinkle,Eric Boerwinkle +16 more
TL;DR: The Mercury analysis pipeline is developed and deployed in local hardware and the Amazon Web Services cloud via the DNAnexus platform and provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts.
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Omic and Electronic Health Record Big Data Analytics for Precision Medicine
TL;DR: This work provides two case studies, including identifying disease biomarkers from multi-omic data and incorporating –omic information into EHR, to demonstrate how big data analytics enables precision medicine.
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Genotyping-by-sequencing approaches to characterize crop genomes: choosing the right tool for the right application
TL;DR: The most common genotyping methods used today are reviewed and compare their suitability for linkage mapping, genomewide association studies (GWAS), marker‐assisted and genomic selection and genome assembly and improvement in crops with various genome sizes and complexity.
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A Proposed Solution and Future Direction for Blockchain-Based Heterogeneous Medicare Data in Cloud Environment
TL;DR: A Blockchain-based platform is proposed that can be used for storing and managing electronic medical records in a Cloud environment that makes the work easier, keeps an eye on the security and accuracy of the data and also reduces the cost of maintenance.
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.