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An open API service providing mapping between scientific papers and software projects that are mentioned in them.

Papers: 10.1186/s13040-020-00213-y

https://doi.org/10.1186/s13040-020-00213-y

Ideas for how informaticians can get involved with COVID-19 research

Cited by: 17
Author(s): Jason H. Moore, Ian Barnett, Mary Regina Boland, Yong Chen, George Demiris, Graciela Gonzalez-Hernandez, Daniel S. Herman, Blanca E. Himes, Rebecca A. Hubbard, Dokyoon Kim, Jeffrey S. Morris, Danielle L. Mowery, Marylyn D. Ritchie, Li Shen, Ryan J. Urbanowicz, John H. Holmes
Published: about 5 years ago

Software Mentions 9

cran: mada
Meta-Analysis of Diagnostic Accuracy
Papers that mentioned: 78
Very Likely Science (85)
cran: meta
General Package for Meta-Analysis
Papers that mentioned: 706
Very Likely Science (100)
cran: metafor
Meta-Analysis Package for R
Papers that mentioned: 1,205
Very Likely Science (100)
cran: metasens
Statistical Methods for Sensitivity Analysis in Meta-Analysis
Papers that mentioned: 14
Very Likely Science (100)
cran: mvmeta
Multivariate and Univariate Meta-Analysis and Meta-Regression
Papers that mentioned: 112
Very Likely Science (93)
cran: netmeta
Network Meta-Analysis using Frequentist Methods
Papers that mentioned: 136
Very Likely Science (100)
cran: xmeta
A Toolbox for Multivariate Meta-Analysis
Papers that mentioned: 2
Very Likely Science (85)
pypi: meta
Byte-code and ast programming tools
Papers that mentioned: 706
Very Likely Science (80)
pypi: scikit-learn
A set of python modules for machine learning and data mining
Papers that mentioned: 2,431
Very Likely Science (100)