There are several indices that provide an indication of different types on the performance of QSAR classification models, being the area under a Receiver Operating Characteristic (ROC) curve still the most powerful test to overall assess such performance. All ROC related parameters can be calculated for both the training and test sets, but, nevertheless, neither of them constitutes an absolute indicator of the classification performance by themselves. Moreover, one of the biggest drawbacks is the computing time needed to obtain the area under the ROC curve, which naturally slows down any calculation algorithm. The present study proposes two new parameters based on distances in a ROC curve for the selection of classification models with an appropriate balance in both training and test sets, namely the following: the ROC graph Euclidean distance (ROCED) and the ROC graph Euclidean distance corrected with Fitness Function (FIT(λ)) (ROCFIT). The behavior of these indices was observed through the study on the mutagenicity for four genotoxicity end points of a number of nonaromatic halogenated derivatives. It was found that the ROCED parameter gets a better balance between sensitivity and specificity for both the training and prediction sets than other indices such as the Matthews correlation coefficient, the Wilk's lambda, or parameters like the area under the ROC curve. However, when the ROCED parameter was used, the follow-on linear discriminant models showed the lower statistical significance. But the other parameter, ROCFIT, maintains the ROCED capabilities while improving the significance of the models due to the inclusion of FIT(λ).
Learning chemical nomenclature is part of many students' first contact with chemistry. Generation after generation of students has come to love chemistry after successfully overcoming the "barriers" of the first difficulties in the learning process. Other students fail and abandon the study of chemistry forever. A tool named FORMula, which is a combination of the words FORM (i.e., shape) and formula, has been developed to reduce or eliminate barriers in the process of learning inorganic chemistry nomenclature. The method uses two-dimensional polygonal or circular shapes and panels (representing ions) that can be assembled only in ways permitted by the rules of nomenclature to create compounds. This method can be used to help students in determining the name of a compound given its chemical formula and in determining a chemical formula of a compound when given its name. This method can help any new chemistry student, but particularly students affected by color-vision deficiencies, severe visual impairments, or blindness. Students can practice individually or in groups, in the classroom or at home. The method can also be used to help understand the periodic table, element properties (such as oxidation states), the stoichiometries of chemical reactions, and the application of nomenclature rules in inorganic chemistry.
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