Login / Signup

Predicting hydration free energies of polychlorinated aromatic compounds from the SAMPL-3 data set with FiSH and LIE models.

Traian SuleaEnrico O. Purisima
Published in: J. Comput. Aided Mol. Des. (2012)
Keyphrases
  • data sets
  • experimental data
  • real world
  • higher order
  • training set
  • high dimensional data
  • computational models
  • database
  • case study
  • training data
  • graph cuts
  • gene expression data