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eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates.

Limeng PuMisagh NaderiTairan LiuHsiao-Chun WuSupratik MukhopadhyayMichal Brylinski
Published in: BMC pharmacology & toxicology (2019)
eToxPred can be incorporated into protocols to construct custom libraries for virtual screening in order to filter out those drug candidates that are potentially toxic or would be difficult to synthesize. It is freely available as a stand-alone software at https://github.com/pulimeng/etoxpred .
Keyphrases
  • machine learning
  • oxidative stress
  • artificial intelligence
  • big data
  • data analysis
  • electronic health record
  • oxide nanoparticles