INVESTIGADORES
PONZONI Ignacio
congresos y reuniones científicas
Título:
A Genetic Algorithm for Detection of Relevant Descriptors in ADMET Prediction
Autor/es:
CECCHINI, ROCÍO L.; SOTO, AXEL J.; VAZQUEZ, GUSTAVO E.; PONZONI IGNACIO
Lugar:
Río de Janeiro, Brasil
Reunión:
Simposio; Brazilian Symposium on Bioinformatics (BSB 2007); 2007
Institución organizadora:
SBC (Sociedad Brasilera de Computación).
Resumen:
In this work, a novel approach for descriptor selection aimed to physicochemical property prediction is presented. The capacity of determining the most significant set of descriptors is of great importance due to their contribution for improving ADMET prediction models. The proposed methodology combines a genetic algorithm with decision trees. Experimental analysis was carried out for predicting the octanol-water partition coefficient (logP) using neural networks as prediction method. The performance results showed the good potential of this technique.
