Journal
JOURNAL OF CHEMICAL INFORMATION AND MODELING
Volume 45, Issue 3, Pages 800-806Publisher
AMER CHEMICAL SOC
DOI: 10.1021/ci050022a
Keywords
-
Ask authors/readers for more resources
We present a method to measure the relative importance of the descriptors present in a QSAR model developed with a computational neural network (CNN). The approach is based on a sensitivity analysis of the descriptors. We tested the method on three published data sets for which linear and CNN models were previously built. The original work reported interpretations for the linear models, and we compare the results of the new method to the importance of descriptors in the linear models as described by a PLS technique. The results indicate that the proposed method is able to rank descriptors such that important descriptors in the CNN model correspond to the important descriptors in the linear model.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available