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Papers: 10.1186/s12943-021-01405-8

https://doi.org/10.1186/s12943-021-01405-8

Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality

Cited by: 6
Author(s): Salvatore Benfatto, Özdemirhan Serçin, Francesca R. Dejure, Amir Abdollahi, Frank T. Zenke, Balca R. Mardin
Published: almost 4 years ago

Software Mentions 9

bioconductor: DESeq2
Differential gene expression analysis based on the negative binomial distribution
Papers that mentioned: 9,583
Very Likely Science (100)
bioconductor: STRINGdb
STRINGdb - Protein-Protein Interaction Networks and Functional Enrichment Analysis
Papers that mentioned: 82
Very Likely Science (100)
cran: Boruta
Wrapper Algorithm for All Relevant Feature Selection
Papers that mentioned: 192
Very Likely Science (93)
cran: ranger
A Fast Implementation of Random Forests
Papers that mentioned: 91
Very Likely Science (100)
cran: shiny
Web Application Framework for R
Papers that mentioned: 127
Very Likely Science (100)
cran: visNetwork
Network Visualization using 'vis.js' Library
Papers that mentioned: 49
Very Likely Science (100)
pypi: Boruta
Python Implementation of Boruta Feature Selection
Papers that mentioned: 192
Very Likely Science (80)
pypi: ranger
A Python package for the manipulation of Range objects
Papers that mentioned: 91
Very Likely Science (100)
pypi: shiny
A web development framework for Python.
Papers that mentioned: 127
Very Likely Science (100)