Data reduction and representation in drug discovery

摘要: Pre-clinical drug discovery relies increasingly on huge volumes of inter-related multivariate data. To make sense these data and enable quality decision-making based this plethora information they must be presented in an interpretable form. Reducing the dimensionality often leaves a set that is too complex to interpret readily, so intuitive visualization methods are needed. Bioinformatics has provided much impetus for visualizing data, cheminformatics community been aggressive with data-reduction problem. The increasing appreciation multifactorial nature pre-clinical makes burgeoning active field spans biosciences, mathematics visual psychology.