Unknown

Dataset Information

0

ToxCast EPA in Vitro to in Vivo Challenge: Insight into the Rank-I Model.


ABSTRACT: The ToxCast EPA challenge was managed by TopCoder in Spring 2014. The goal of the challenge was to develop a model to predict the lowest effect level (LEL) concentration based on in vitro measurements and calculated in silico descriptors. This article summarizes the computational steps used to develop the Rank-I model, which calculated the lowest prediction error for the secret test data set of the challenge. The model was developed using the publicly available Online CHEmical database and Modeling environment (OCHEM), and it is freely available at http://ochem.eu/article/68104 . Surprisingly, this model does not use any in vitro measurements. The logic of the decision steps used to develop the model and the reason to skip inclusion of in vitro measurements is described. We also show that inclusion of in vitro assays would not improve the accuracy of the model.

SUBMITTER: Novotarskyi S 

PROVIDER: S-EPMC5413193 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

altmetric image

Publications

ToxCast EPA in Vitro to in Vivo Challenge: Insight into the Rank-I Model.

Novotarskyi Sergii S   Abdelaziz Ahmed A   Sushko Yurii Y   Körner Robert R   Vogt Joachim J   Tetko Igor V IV  

Chemical research in toxicology 20160427 5


The ToxCast EPA challenge was managed by TopCoder in Spring 2014. The goal of the challenge was to develop a model to predict the lowest effect level (LEL) concentration based on in vitro measurements and calculated in silico descriptors. This article summarizes the computational steps used to develop the Rank-I model, which calculated the lowest prediction error for the secret test data set of the challenge. The model was developed using the publicly available Online CHEmical database and Model  ...[more]

Similar Datasets

| S-EPMC5351294 | biostudies-literature
| S-EPMC8144460 | biostudies-literature
| S-EPMC2565905 | biostudies-literature
| S-EPMC9290695 | biostudies-literature
| S-EPMC3226507 | biostudies-literature
| S-EPMC1135795 | biostudies-other
| S-EPMC8059620 | biostudies-literature
| S-EPMC6933417 | biostudies-literature
| S-EPMC11300212 | biostudies-literature
| S-EPMC5442248 | biostudies-literature