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

Papers: 10.1155/2019/8418760

https://doi.org/10.1155/2019/8418760

Integrative Deep Learning for Identifying Differentially Expressed (DE) Biomarkers

Cited by: 8
Author(s): Jayeon Lim, SoYoun Bang, Jiyeon Kim, Cheolyong Park, JunSang Cho, Sunghwan Kim
Published: over 5 years ago

Software Mentions 7

cran: coda
Output Analysis and Diagnostics for MCMC
Papers that mentioned: 126
Very Likely Science (85)
cran: doMC
Foreach Parallel Adaptor for 'parallel'
Papers that mentioned: 27
Very Likely Science (75)
cran: e1071
Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien
Papers that mentioned: 419
Very Likely Science (85)
cran: MASS
Support Functions and Datasets for Venables and Ripley's MASS
Papers that mentioned: 2,353
Very Likely Science (100)
cran: MCMCpack
Markov Chain Monte Carlo (MCMC) Package
Papers that mentioned: 40
Very Likely Science (83)
pypi: coda
File metadata tagging and organization.
Papers that mentioned: 126
Very Likely Science (80)
pypi: metalogistic
A Python package for the metalogistic distribution. The metalogistic or metalog distribution is a highly flexible probability distribution that can be used to model data without traditional parameters.
Papers that mentioned: 1
Very Likely Science (65)