Predicting Physical-Chemical Properties of Compounds from Molecular Structures by Recursive Neural Networks

@article{Bernazzani2006PredictingPP,
  title={Predicting Physical-Chemical Properties of Compounds from Molecular Structures by Recursive Neural Networks},
  author={Luca Bernazzani and Celia Duce and Alessio Micheli and Vincenzo Mollica and Alessandro Sperduti and Antonina Starita and Maria Rosaria Tin{\'e}},
  journal={Journal of chemical information and modeling},
  year={2006},
  volume={46 5},
  pages={
          2030-42
        }
}
In this paper, we report on the potential of a recently developed neural network for structures applied to the prediction of physical chemical properties of compounds. The proposed recursive neural network (RecNN) model is able to directly take as input a structured representation of the molecule and to model a direct and adaptive relationship between the molecular structure and target property. Therefore, it combines in a learning system the flexibility and general advantages of a neural… CONTINUE READING

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