Segregating confident predictions of chemicals' properties for virtual screening of drugs

Axel J. Soto, Ignacio Ponzoni, Gustavo E. Vazquez

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

3 Citas (Scopus)

Resumen

In this paper we present a methodology for evaluating the confidence in the prediction of a physicochemical or biological property. Identifying unreliable compounds' predictions is crucial for the modern drug discovery process.This task is accomplished by the combination of the method of prediction with a self-organizing map. In this way, the method is able to segregate unconfident predictions as well as confident predictions. We applied the method to four different data sets, and we obtained significant differences in the average predictions of our segregation. This approach constitutes a novel way for evaluating confidence, since it not only looks for extrapolation situations but also it identifies interpolation problems.

Idioma originalInglés
Título de la publicación alojadaDistributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings
Páginas1005-1012
Número de páginas8
EdiciónPART 2
DOI
EstadoPublicada - 2009
Publicado de forma externa
Evento10th International Work-Conference on Artificial Neural Networks, IWANN 2009 - Salamanca
Duración: 10 jun. 200912 jun. 2009

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NúmeroPART 2
Volumen5518 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia10th International Work-Conference on Artificial Neural Networks, IWANN 2009
País/TerritorioSpain
CiudadSalamanca
Período10/06/0912/06/09

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