DARTpaths
DARTpaths predicts developmental and reproductive toxicity (DART) by applying Xpaths algorithms to integrate phenotypic endpoints across multiple species and infer compound-induced molecular mechanisms of action.
Key Features:
- DART prediction: Predicts developmental and reproductive toxicity (DART) for compounds using integrated phenotypic data.
- Xpaths algorithms: Applies advanced algorithms known as Xpaths for in silico analysis of toxicity-related pathways.
- Cross-species phenotypic integration: Integrates phenotypic endpoints across multiple species to enable cross-species inference.
- Mechanism inference: Infers compound-induced molecular mechanisms of action from integrated phenotypic endpoints.
- Follow-up test proposals: Proposes follow-up tests for model organisms to validate predicted pathways.
Scientific Applications:
- Toxicological studies: Supports toxicological studies of developmental and reproductive endpoints by identifying potential adverse effects and underlying mechanisms.
- Safer drug development: Informs safer drug development by highlighting compounds with predicted DART liabilities and their mechanisms of action.
- Chemical assessment: Aids chemical assessment processes by providing mechanistic predictions of developmental and reproductive toxicity across species.
Methodology:
Applies Xpaths algorithms to integrate cross-species phenotypic endpoints, infer compound-induced molecular mechanisms of action, and propose model-organism follow-up tests.
Topics
Details
- License:
- Apache-2.0
- Cost:
- Free of charge (with restrictions)
- Tool Type:
- web application
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- R
- Added:
- 2/19/2023
- Last Updated:
- 11/24/2024
Operations
Publications
Bhalla D, Steijaert MN, Poppelaars ES, Teunis M, van der Voet M, Corradi M, Dévière E, Noothout L, Tomassen W, Rooseboom M, Currie RA, Krul C, Pieters R, van Noort V, Wildwater M. DARTpaths, an<i>in silico</i>platform to investigate molecular mechanisms of compounds. Bioinformatics. 2022;39(1). doi:10.1093/bioinformatics/btac767. PMID:36477801. PMCID:PMC9825785.