Analysis of the benefits of imputation models over traditional QSAR models for toxicity prediction.

ABSTRACT: Recently, imputation techniques have been adapted to predict activity values among sparse bioactivity matrices, showing improvements in predictive performance over traditional QSAR models. These models are able to use experimental activity values for auxiliary assays when predicting the activity of a test compound on a specific assay. In this study, we tested three different multi-task imputation techniques on three classification-based toxicity datasets: two of small scale (12 assays each) and one large scale with 417 assays. Moreover, we analyzed in detail the improvements shown by the imputation models. We found that test compounds that were dissimilar to training compounds, as well as test compounds with a large number of experimental values for other assays, showed the largest improve

SUBMITTER: Walter M 

PROVIDER: S-EPMC9172131 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature