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Adaptive modelling of structured molecular representations for toxicity prediction.
- Source :
-
AIP Conference Proceedings . Dec2012, Vol. 1504 Issue 1, p721-724. 4p. 1 Diagram, 1 Graph. - Publication Year :
- 2012
-
Abstract
- We investigated the possibility of modelling structure-toxicity relationships by direct treatment of the molecular structure (without using descriptors) through an adaptive model able to retain the appropriate structural information. With respect to traditional descriptor-based approaches, this provides a more general and flexible way to tackle prediction problems that is particularly suitable when little or no background knowledge is available. Our method employs a tree-structured molecular representation, which is processed by a recursive neural network (RNN). To explore the realization of RNN modelling in toxicological problems, we employed a data set containing growth impairment concentrations (IGC50) for Tetrahymena pyriformis. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0094243X
- Volume :
- 1504
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- AIP Conference Proceedings
- Publication Type :
- Conference
- Accession number :
- 84140480
- Full Text :
- https://doi.org/10.1063/1.4771796