Difference between revisions of "Book:LIMSjournal - Spring 2017"
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;1. Big data, informatics, and research | ;1. Big data, informatics, and research | ||
:[[Journal:Ten simple rules to enable multi-site collaborations through data sharing|Ten simple rules to enable multi-site collaborations through data sharing (Boland ''et al.'' 2017]] | :[[Journal:Ten simple rules to enable multi-site collaborations through data sharing|Ten simple rules to enable multi-site collaborations through data sharing (Boland ''et al.'' 2017)]] | ||
:[[Journal:A metadata-driven approach to data repository design|A metadata-driven approach to data repository design (Harvey ''et al.'' 2017)]] | :[[Journal:A metadata-driven approach to data repository design|A metadata-driven approach to data repository design (Harvey ''et al.'' 2017)]] | ||
:[[Journal:Data and metadata brokering – Theory and practice from the BCube Project|Data and metadata brokering – Theory and practice from the BCube Project (Khalsa 2017)]] | :[[Journal:Data and metadata brokering – Theory and practice from the BCube Project|Data and metadata brokering – Theory and practice from the BCube Project (Khalsa 2017)]] | ||
:[[Journal:Ten simple rules for cultivating open science and collaborative R&D|Ten simple rules for cultivating open science and collaborative R&D (Masum ''et al.'' 2013)]] | :[[Journal:Ten simple rules for cultivating open science and collaborative R&D|Ten simple rules for cultivating open science and collaborative R&D (Masum ''et al.'' 2013)]] | ||
;2. Bioinformatics | ;2. Bioinformatics | ||
:[[Journal:PCM-SABRE: A platform for benchmarking and comparing outcome prediction methods in precision cancer medicine|PCM-SABRE: A platform for benchmarking and comparing outcome prediction methods in precision cancer medicine (Eyal-Altman ''et al.'' 2017)]] | :[[Journal:PCM-SABRE: A platform for benchmarking and comparing outcome prediction methods in precision cancer medicine|PCM-SABRE: A platform for benchmarking and comparing outcome prediction methods in precision cancer medicine (Eyal-Altman ''et al.'' 2017)]] | ||
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:[[Journal:DGW: An exploratory data analysis tool for clustering and visualisation of epigenomic marks|DGW: An exploratory data analysis tool for clustering and visualisation of epigenomic marks (Lukauskas ''et al.'' 2016)]] | :[[Journal:DGW: An exploratory data analysis tool for clustering and visualisation of epigenomic marks|DGW: An exploratory data analysis tool for clustering and visualisation of epigenomic marks (Lukauskas ''et al.'' 2016)]] | ||
:[[Journal:Use of application containers and workflows for genomic data analysis|Use of application containers and workflows for genomic data analysis (Schulz ''et al.'' 2016)]] | :[[Journal:Use of application containers and workflows for genomic data analysis|Use of application containers and workflows for genomic data analysis (Schulz ''et al.'' 2016)]] | ||
;3. Health, public health, and clinical informatics | ;3. Health, public health, and clinical informatics | ||
:[[Journal:Informatics metrics and measures for a smart public health systems approach: Information science perspective|Informatics metrics and measures for a smart public health systems approach: Information science perspective (Carney and Shea 2017)]] | :[[Journal:Informatics metrics and measures for a smart public health systems approach: Information science perspective|Informatics metrics and measures for a smart public health systems approach: Information science perspective (Carney and Shea 2017)]] | ||
Latest revision as of 14:59, 7 December 2018
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LIMSjournal - Spring 2017: Volume 3, Issue 1
This collection of 12 open-access journal articles loaded to LIMSwiki in January–March 2017 is compiled as a convenient, easy-to-access compilation. It is organized alphabetically by topic and then by author, with the author and publication year appearing at the end for your convenience.
- 1. Big data, informatics, and research
- Ten simple rules to enable multi-site collaborations through data sharing (Boland et al. 2017)
- A metadata-driven approach to data repository design (Harvey et al. 2017)
- Data and metadata brokering – Theory and practice from the BCube Project (Khalsa 2017)
- Ten simple rules for cultivating open science and collaborative R&D (Masum et al. 2013)
- 2. Bioinformatics
- PCM-SABRE: A platform for benchmarking and comparing outcome prediction methods in precision cancer medicine (Eyal-Altman et al. 2017)
- SCIFIO: An extensible framework to support scientific image formats (Hiner et al. 2017)
- Ten simple rules for developing usable software in computational biology (List et al. 2017)
- DGW: An exploratory data analysis tool for clustering and visualisation of epigenomic marks (Lukauskas et al. 2016)
- Use of application containers and workflows for genomic data analysis (Schulz et al. 2016)
- 3. Health, public health, and clinical informatics
- Informatics metrics and measures for a smart public health systems approach: Information science perspective (Carney and Shea 2017)
- Deployment of analytics into the healthcare safety net: Lessons learned (Hartzband and Jacobs 2016)
- The effect of the General Data Protection Regulation on medical research (Rumbold and Pierscionek 2017)
