EDTox: an R Shiny application to predict the endocrine disruption potential of compounds.

ABSTRACT:

Purpose

Endocrine disruptors are a rising concern due to the wide array of health issues that it can cause. Although there are tools for mode of action (MoA)-based prediction of endocrine disruption (e.g. QSAR Toolbox and iSafeRat), none of them is based on toxicogenomics data. Here, we present EDTox, an R Shiny application enabling users to explore and use a computational method that we have recently published to identify and prioritize endocrine disrupting (ED) chemicals based on toxicogenomic data. The EDTox pipeline utilizes previously trained toxicogenomic-driven classifiers to make predictions on new untested compounds by using their molecular initiating events. Furthermore, the proposed R Shiny app allows users to extend the prediction systems by training and adding new clas

SUBMITTER: Sakhteman A 

PROVIDER: S-EPMC8963299 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature