Papers: 10.1371/journal.pone.0196865

https://doi.org/10.1371/journal.pone.0196865

Predicting potential drug-drug interactions on topological and semantic similarity features using statistical learning

Cited by: 89
Author(s): Andrej Kastrin, Polonca Ferk, Brane Leskošek
Published: over 8 years ago

Software Mentions 8

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: gbm
Generalized Boosted Regression Models
Papers that mentioned: 250
Very Likely Science (100)
cran: rcdk
Interface to the 'CDK' Libraries
Papers that mentioned: 30
Very Likely Science (75)
cran: ROSE
Random Over-Sampling Examples
Papers that mentioned: 131
Very Likely Science (75)
cran: rpart
Recursive Partitioning and Regression Trees
Papers that mentioned: 431
Very Likely Science (100)
pypi: gbm
Read and analyze GBM data
Papers that mentioned: 250
Very Likely Science (100)
pypi: language
Basic tools for working with natural language text data
Papers that mentioned: 427
Very Likely Science (65)