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Visual analytics in cheminformatics: user-supervised descriptor selection for QSAR methods by María Jimena Martínez; Ignacio Ponzoni; Mónica F Díaz; Gustavo E Vazquez; Axel J Soto is a Computer Science article available to read on EtoBox.

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## Background 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. ## Results In this paper a software tool, which we named Visual and Interactive DEscriptor ANalysis (VIDEAN), that combines statistical methods with interactive visualizations for choosing a set of descriptors for predicting a target property is proposed. Domain expertise can be added to the feature selection process by means of an interactive visual exploration of data, and aided by statistical tools and metrics based on information theory. Coordinated visual representations are presented for capturing different relatio

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Author

María Jimena Martínez; Ignacio Ponzoni; Mónica F Díaz; Gustavo E Vazquez; Axel J Soto

Publisher

Springer Science and Business Media LLC

Published

2015

Language

EN

Field

Computer Science (Physical Sciences)