Special Issue "QSAR and Chemoinformatics Tools for Modeling"
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".
Deadline for manuscript submissions: closed (31 October 2019) | Viewed by 67024
Special Issue Editor
Interests: chemometric; QSAR/QSPR; multi-criteria decision making; molecular descriptors; software development
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the past decade, quantitative structure–activity relationships (QSARs) have become a well-established field of scientific research, a field where many different mathematical tools are applied to detect predictive relationships between molecular structure and pharmacological activities, toxicological/ecotoxicological properties, and adverse effects of molecules on human health.
In the proposed Special Issue, the main idea is not only to present QSAR results on new datasets/modelling campaigns, but also to compare different chemometric and chemoinformatic tools on benchmark data sets, especially including (together with the classical regression and classification methods) read-across approaches, ranking models, machine learning, and deep learning methods.
Authors are also invited to pay attention to the concept of the applicability domain of the models, their prediction ability, and models obtained by data fusion and consensus approaches.
Molecular applications aimed to model endocrine disruptors effects, carcinogenicity, and mutagenicity as well as studies on omics data will be particularly appreciated.
Prof. Dr. Roberto Todeschini
Guest Editor
Manuscript Submission Information
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Keywords
- QSAR
- QSPR
- chemometrics
- chemoinformatics
- machine learning
- applicability domain
- regression models
- classification models
- ranking models
- consensus models
- molecular descriptors
- omics data
- endocrine disruptors
- carcinogenicity
- mutagenicity