Abstract:
:The selection of the most relevant molecular descriptors to describe a target variable in the context of QSAR (Quantitative Structure-Activity Relationship) modelling is a challenging combinatorial optimization problem. In this paper, a novel software tool for addressing this task in the context of regression and classification modelling is presented. The methodology that implements the tool is organized into two phases. The first phase uses a multiobjective evolutionary technique to perform the selection of subsets of descriptors. The second phase performs an external validation of the chosen descriptors subsets in order to improve reliability. The tool functionalities have been illustrated through a case study for the estimation of the ready biodegradation property as an example of classification QSAR modelling. The results obtained show the usefulness and potential of this novel software tool that aims to reduce the time and costs of development in the drug discovery process.
journal_name
Biomed Res Intjournal_title
BioMed research internationalauthors
Martínez MJ,Razuc M,Ponzoni Idoi
10.1155/2019/2905203subject
Has Abstractpub_date
2019-02-17 00:00:00pages
2905203eissn
2314-6133issn
2314-6141journal_volume
2019pub_type
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pub_type: 杂志文章,随机对照试验
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pub_type: 杂志文章
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