Feature optimization in high dimensional chemical space: statistical and data mining solutions.

ABSTRACT:

Objectives

The primary goal of this experiment is to prioritize molecular descriptors that control the activity of active molecules that could reduce the dimensionality produced during the virtual screening process. It also aims to: (1) develop a methodology for sampling large datasets and the statistical verification of the sampling process, (2) apply screening filter to detect molecules with polypharmacological or promiscuous activity.

Results

Sampling from large a dataset and its verification were done by applying Z-test. Molecular descriptors were prioritized using principal component analysis (PCA) by eliminating the least influencing ones. The original dimensions were reduced to one-twelfth by the application of PCA. There was a significant improvement in statistical p

SUBMITTER: K R J 

PROVIDER: S-EPMC6044099 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature