Biodegradability is a key property
in the development of safer
fragrances. In this work we present a green methodology for its preliminary
assessment. The structure of various fragrant molecules is characterized
by computing a large set of topological indices. Those relevant to
biodegradability are selected by means of a hybrid stepwise selection
method to build a linear classifier. This model is compared with a
more complex artificial neural network trained with the indices previously
found. After validation, the models show promise for time and cost
reduction in the development of new, safer fragrances. The methodology
presented could easily be adapted to many quasi-big data problems
in R&D environments.
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