INVESTIGADORES
DIAZ Monica Fatima
artículos
Título:
Visual Analytics in Cheminformatics: User-Supervised Descriptor Selection for QSAR Methods
Autor/es:
MARÍA JIMENA MARTÍNEZ; IGNACIO PONZONI; MONICA F. DIAZ; GUSTAVO E. VAZQUEZ; AXEL J. SOTO
Revista:
Journal of cheminformatics
Editorial:
Chemistry Central C/o Biomed Central
Referencias:
Lugar: London; Año: 2015 vol. 7
ISSN:
1758-2946
Resumen:
The design of QSAR/QSPR models is a challenging problem, where the selection of the most relevant descriptors constitutes a key step of the process. Several feature selection methods that address this step are concentrated on statistical associations among descriptors and target properties, whereas the chemical knowledge is left out of the analysis. For this reason, the interpretability and generality of the QSAR/QSPR models obtained by these feature selection methods are drastically affected. Therefore, an approach for integrating domain expert?s knowledge in the selection process is needed for increase the confidence in the final set of descriptors.
