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

Papers: 10.3390/ijms22031075

https://doi.org/10.3390/ijms22031075

A Novel Epigenetic Machine Learning Model to Define Risk of Progression for Hepatocellular Carcinoma Patients

Cited by: 7
Author(s): Luca Bedon, Michele Dal Bo, Monica Mossenta, Davide Busato, Giuseppe Toffoli, Maurizio Polano
Published: over 4 years ago

Software Mentions 13

bioconductor: clusterProfiler
A universal enrichment tool for interpreting omics data
Papers that mentioned: 2,223
Very Likely Science (75)
bioconductor: DESeq2
Differential gene expression analysis based on the negative binomial distribution
Papers that mentioned: 9,583
Very Likely Science (100)
bioconductor: DOSE
Disease Ontology Semantic and Enrichment analysis
Papers that mentioned: 138
Very Likely Science (100)
bioconductor: goseq
Gene Ontology analyser for RNA-seq and other length biased data
Papers that mentioned: 132
Very Likely Science (100)
cran: Boruta
Wrapper Algorithm for All Relevant Feature Selection
Papers that mentioned: 192
Very Likely Science (93)
cran: caret
Classification and Regression Training
Papers that mentioned: 630
Very Likely Science (100)
cran: ggplot2
Create Elegant Data Visualisations Using the Grammar of Graphics
Papers that mentioned: 11,441
Very Likely Science (100)
cran: MASS
Support Functions and Datasets for Venables and Ripley's MASS
Papers that mentioned: 2,353
Very Likely Science (100)
cran: pheatmap
Pretty Heatmaps
Papers that mentioned: 2,572
Very Likely Science (75)
cran: ranger
A Fast Implementation of Random Forests
Papers that mentioned: 91
Very Likely Science (100)
pypi: Boruta
Python Implementation of Boruta Feature Selection
Papers that mentioned: 192
Very Likely Science (80)
pypi: caret
A Python Interface to Asterisk
Papers that mentioned: 630
Very Likely Science (65)
pypi: ranger
A Python package for the manipulation of Range objects
Papers that mentioned: 91
Very Likely Science (100)