Convolutional neural network model based on 2d fingerprint for bioactivity prediction

HIGHLIGHTS

• who: Hamza Hentabli and colleagues from the Laboratory of Advanced Electronics Systems (LSEA), University of Medea, Medea, Algeria Malaysia, Johor Bahru, Johor, Malaysia have published the paper: Convolutional Neural Network Model Based on 2D Fingerprint for Bioactivity Prediction, in the Journal: (JOURNAL)
• what: In this paper a novel technique based on a deep learning neural network (CNN) for the prediction of chemical compounds` bioactivity is proposed and developed. In this study, eight different 2D fingerprints were investigated for bioactivity prediction, which was generated using the PaDEL descriptor software. This study used three datasets , which were . . .
  

   

  

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