ArticleBioinformatics (Oxford, England)2016
cl-dash: rapid configuration and deployment of Hadoop clusters for bioinformatics research in the cloud.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Load Balancing Algorithms for Hadoop Cluster in Unbalanced Environment.Computational intelligence and neuroscience · 2022Article
- A Genocentric Approach to Discovery of Mendelian Disorders.American journal of human genetics · 2019Article
- Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets.Nature methods · 2016Article
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Authors and funding
4 authors.
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Abstract
unlabelled: One of the solutions proposed for addressing the challenge of the overwhelming abundance of genomic sequence and other biological data is the use of the Hadoop computing framework. Appropriate tools are needed to set up computational environments that facilitate research of novel bioinformatics methodology using Hadoop. Here, we present cl-dash, a complete starter kit for setting up such an environment. Configuring and deploying new Hadoop clusters can be done in minutes. Use of Amazon Web Services ensures no initial investment and minimal operation costs. Two sample bioinformatics applications help the researcher understand and learn the principles of implementing an algorithm using the MapReduce programming pattern. AVAILABILITY AND IMPLEMENTATION: Source code is available at https://bitbucket.org/booz-allen-sci-comp-team/cl-dash.git. CONTACT: hodor_paul@bah.com.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.