Prediction of tumoricidal activity and accumulation of photosensitizers in photodynamic therapy using multiple linear regression and artificial neural networks.

@article{Vanyrr2002PredictionOT,
  title={Prediction of tumoricidal activity and accumulation of photosensitizers in photodynamic therapy using multiple linear regression and artificial neural networks.},
  author={R Vanyr{\'u}r and K{\'a}roly H{\'e}berger and Istv{\'a}n K{\"o}vesdi and Judit Jakus},
  journal={Photochemistry and photobiology},
  year={2002},
  volume={75 5},
  pages={471-8}
}
The biological activities of a congeneric series of pyropheophorbides used as sensitizers in photodynamic therapy have been predicted on the basis of their molecular structures, using multiple linear regression and artificial neural network (ANN) computations. Theoretical descriptors (a total of 81) were calculated by the 3DNET program based on the three-dimensional structure (3D) of the geometry-optimized molecules. These input descriptors were tested as independent variables and used for… CONTINUE READING