On two novel parameters for validation of predictive QSAR models.

ABSTRACT: Validation is a crucial aspect of quantitative structure-activity relationship (QSAR) modeling. The present paper shows that traditionally used validation parameters (leave-one-out Q(2) for internal validation and predictive R(2) for external validation) may be supplemented with two novel parameters r(m)(2) and R(p)(2) for a stricter test of validation. The parameter r(m)(2)((overall)) penalizes a model for large differences between observed and predicted values of the compounds of the whole set (considering both training and test sets) while the parameter R(p)(2) penalizes model R(2) for large differences between determination coefficient of nonrandom model and square of mean correlation coefficient of random models in case of a randomization test. Two other variants of r(m)(2) parameter,

SUBMITTER: Pratim Roy P 

PROVIDER: S-EPMC6254296 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature