DeepTox: Toxicity Prediction using Deep Learning
Johannes Kepler University of Linz · RISC Software (Austria)
Abstract
The Tox21 Data Challenge has been the largest effort of the scientific community to compare computational methods for toxicity prediction. This challenge comprised 12,000 environmental chemicals and drugs which were measured for 12 different toxic effects by specifically designed assays. We participated in this challenge to assess the performance of Deep Learning in computational toxicity prediction. Deep Learning has already revolutionized image processing, speech recognition, and language understanding but has not yet been applied to computational toxicity. Deep Learning is founded on novel algorithms and architectures for artificial neural networks together with the recent availability of very fast…
Citation impact
- FWCI
- 84.71
- Percentile
- 100%
- References
- 107
Authors
4Topics & keywords
- Deep learning
- Artificial intelligence
- Machine learning
- Computer science
- Chemical toxicity
- Artificial neural network
- Computational model
- Pipeline (software)