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Papers by Roberto Todeschini

Research paper thumbnail of New fitness functions to avoid bad regression models in variable subset selection by Genetic Algorithms

Research paper thumbnail of Parsimonious optimization of multitask neural network hyperparameters

Research paper thumbnail of Chemometric approaches in environmental problems concerning PCDD and PCDF. Data interpretation and source correlation. Mechanisms of formation and destruction in MSW combustion process

Fresenius' journal of analytical chemistry, 1994

The role of multivariate analysis methods in evaluating, rationalizing, and working out complex e... more The role of multivariate analysis methods in evaluating, rationalizing, and working out complex environmental problems is discussed. The discussion is organized in two sections; a literature analysis of the application of chemometric methods to PCDD/PCDF data interpretation and source correlation and a review of the role of chemometric methods in analysing the results obtained by the Authors studying PCDD/PCDF formation and destruction mechanisms in MSW combustion processes.

Research paper thumbnail of Mapping of Activity through Dichotomic Scores (MADS): a new chemoinformatic approach to detect activity-rich structural regions

Journal of Chemometrics, 2018

Research paper thumbnail of Qualitative consensus of QSAR ready biodegradability predictions

Toxicological & Environmental Chemistry, 2017

Research paper thumbnail of Analisi multivariata dei dati

Research paper thumbnail of A QSTR-Based Expert System to Predict Sweetness of Molecules

Frontiers in Chemistry, 2017

This work describes a novel approach based on advanced molecular similarity to predict the sweetn... more This work describes a novel approach based on advanced molecular similarity to predict the sweetness of chemicals. The proposed Quantitative Structure-Taste Relationship (QSTR) model is an expert system developed keeping in mind the five principles defined by the Organization for Economic Cooperation and Development (OECD) for the validation of (Q)SARs. The 649 sweet and non-sweet molecules were described by both conformation-independent extended-connectivity fingerprints (ECFPs) and molecular descriptors. In particular, the molecular similarity in the ECFPs space showed a clear association with molecular taste and it was exploited for model development. Molecules laying in the subspaces where the taste assignation was more difficult were modeled trough a consensus between linear and local approaches (Partial Least Squares-Discriminant Analysis and N-nearest-neighbor classifier). The expert system, which was thoroughly validated through a Monte Carlo procedure and an external set, gave satisfactory results in comparison with the state-of-the-art models. Moreover, the QSTR model can be leveraged into a greater understanding of the relationship between molecular structure and sweetness, and into the design of novel sweeteners.

Research paper thumbnail of Similarity Coefficients for Binary Chemoinformatics Data: Overview and Extended Comparison Using Simulated and Real Data Sets

This paper reports an analysis and comparison of the use of 51 different similarity coefficients ... more This paper reports an analysis and comparison of the use of 51 different similarity coefficients for computing the similarities between binary fingerprints for both simulated and real chemical data sets. Five pairs and a triplet of coefficients were found to yield identical similarity values, leading to the elimination of seven of the coefficients. The remaining 44 coefficients were then compared in two ways: by their theoretical characteristics using simple descriptive statistics, correlation analysis, multidimensional scaling, Hasse diagrams, and the recently described atemporal target diffusion model; and by their effectiveness for similarity-based virtual screening using MDDR, WOMBAT, and MUV data. The comparisons demonstrate the general utility of the well-known Tanimoto method but also suggest other coefficients that may be worthy of further attention.

Research paper thumbnail of A new concept of higher-order similarity and the role of distance/ similarity measures in local classification methods

In this paper, a new concept of similarity is introduced with the aim of detecting higher-order s... more In this paper, a new concept of similarity is introduced with the aim of detecting higher-order similarities among objects, and meta-distances and meta-similarities are derived from it. A total of 100 meta-distances were obtained from a set of ten classical distances and were compared, in terms of classification performances, against classical distance measures. Classification methods based on local similarity analysis and several benchmark datasets were used. In several cases, the non-error rate (NER) of classifiers based on the new meta-distances significantly increased with respect to that of the classical Euclidean distance.

Research paper thumbnail of Quantitative structure–activity relationships to predict sweet and non‑sweet tastes

properly validated through cross-validation and external test sets. The applicability domain of m... more properly validated through cross-validation and external test sets. The applicability domain of models was investigated, and the interpretation of the role of the molecular descriptors in classifying sweet and non-sweet tastes was evaluated. The classification and the performance of the models presented in this paper are simple but accurate. They are based on a relatively small number of descriptors and a straightforward classification approach. The results presented here indicate that the proposed models can be used to accurately select new compounds as potential sweetener candidates.

Research paper thumbnail of QSAR study on the tropospheric degradation of organic compounds

Research paper thumbnail of Study of the POP atmospheric mobility by QSAR approach

Organohalogen Compounds, 1999

Research paper thumbnail of The BEAM-project: prediction and assessment of mixture toxicities in the aquatic environment

Continental Shelf Research, 2003

Freshwater and marine ecosystems are exposed to various multi-component mixtures of pollutants. N... more Freshwater and marine ecosystems are exposed to various multi-component mixtures of pollutants. Nevertheless, most ecotoxicological research and chemicals regulation focus on hazard and exposure assessment of individual substances only, the problem of chemical mixtures in the environment is ignored to a large extent. In contrast, the assessment of combination effects has a long tradition in pharmacology, where mixtures of chemicals are specifically designed to develop new products, e.g. human and veterinary drugs or agricultural and non-agricultural pesticides. In this area, two concepts are frequently used and are thought to describe fundamental relationships between single substance and mixture effects: Independent Action (Response Addition) and Concentration Addition. The question, to what extent these concepts may also be applied in an ecotoxicological and regulatory context may be considered a research topic of major importance, as the concepts would allow to make use of already existing single substance toxicity data for the predictive assessment of mixture toxicities. Two critical knowledge gaps are identified: (a) There is a lack of environmental realism, as a huge part of our current knowledge about the applicability of the concepts is restricted to artificial situations with respect to mixture composition or biological effect assessment. (b) The knowledge on what exactly is needed for using the concepts as tools for the predictive mixture toxicity assessment is insufficient. Both gaps seriously hamper the necessary, scientifically sound consideration of mixture toxicities in a regulatory context.

Research paper thumbnail of N3 and BNN: Two new similarity based classification methods in comparison with other classifiers

Two novel classification methods, called N3 (N-nearest neighbors) and BNN (binned nearest neighbo... more Two novel classification methods, called N3 (N-nearest neighbors) and BNN (binned nearest neighbors), are proposed. Both methods are inspired by the principles of the K-nearest neighbors (KNN) method, being both based on object pairwise similarities. Their performance was evaluated in comparison with nine well-known classification methods. In order to obtain reliable statistics, several comparisons were performed using 32 different literature data sets, which differ for number of objects, variables and classes. Results highlighted that N3 on average behaves as the most efficient classification method with similar performance to support vector machine based on radial basis function kernel (SVM/RBF). The method BNN showed on average higher performance than the classical K-nearest neighbors method.

Research paper thumbnail of BCF Dataset

Research paper thumbnail of Toxicity Data Daphnia

Research paper thumbnail of Generalizing the McClelland Bounds for Total π-Electron Energy

Zeitschrift für Naturforschung A, 2008

In 1971 McClelland obtained lower and upper bounds for the total π-electron energy. We now formul... more In 1971 McClelland obtained lower and upper bounds for the total π-electron energy. We now formulate the generalized version of these bounds, applicable to the energy-like expression

Research paper thumbnail of ATDM(Buscema-Todeschini- JCIM 2012)

This paper reports an analysis and comparison of the use of 51 different similarity coefficients ... more This paper reports an analysis and comparison of the use of 51 different similarity coefficients for computing the similarities between binary fingerprints for both simulated and real chemical data sets. Five pairs and a triplet of coefficients were found to yield identical similarity values, leading to the elimination of seven of the coefficients. The remaining 44 coefficients were then compared in two ways: by their theoretical characteristics using simple descriptive statistics, correlation analysis, multidimensional scaling, Hasse diagrams, and the recently described atemporal target diffusion model; and by their effectiveness for similarity-based virtual screening using MDDR, WOMBAT, and MUV data. The comparisons demonstrate the general utility of the well-known Tanimoto method but also suggest other coefficients that may be worthy of further attention.

Research paper thumbnail of A similarity-based QSAR model for predicting acute toxicity towards the fathead minnow (Pimephales promelas)

Research paper thumbnail of Assessing the validity of QSARs for ready biodegradability of chemicals: An Applicability Domain perspective

Research paper thumbnail of New fitness functions to avoid bad regression models in variable subset selection by Genetic Algorithms

Research paper thumbnail of Parsimonious optimization of multitask neural network hyperparameters

Research paper thumbnail of Chemometric approaches in environmental problems concerning PCDD and PCDF. Data interpretation and source correlation. Mechanisms of formation and destruction in MSW combustion process

Fresenius' journal of analytical chemistry, 1994

The role of multivariate analysis methods in evaluating, rationalizing, and working out complex e... more The role of multivariate analysis methods in evaluating, rationalizing, and working out complex environmental problems is discussed. The discussion is organized in two sections; a literature analysis of the application of chemometric methods to PCDD/PCDF data interpretation and source correlation and a review of the role of chemometric methods in analysing the results obtained by the Authors studying PCDD/PCDF formation and destruction mechanisms in MSW combustion processes.

Research paper thumbnail of Mapping of Activity through Dichotomic Scores (MADS): a new chemoinformatic approach to detect activity-rich structural regions

Journal of Chemometrics, 2018

Research paper thumbnail of Qualitative consensus of QSAR ready biodegradability predictions

Toxicological & Environmental Chemistry, 2017

Research paper thumbnail of Analisi multivariata dei dati

Research paper thumbnail of A QSTR-Based Expert System to Predict Sweetness of Molecules

Frontiers in Chemistry, 2017

This work describes a novel approach based on advanced molecular similarity to predict the sweetn... more This work describes a novel approach based on advanced molecular similarity to predict the sweetness of chemicals. The proposed Quantitative Structure-Taste Relationship (QSTR) model is an expert system developed keeping in mind the five principles defined by the Organization for Economic Cooperation and Development (OECD) for the validation of (Q)SARs. The 649 sweet and non-sweet molecules were described by both conformation-independent extended-connectivity fingerprints (ECFPs) and molecular descriptors. In particular, the molecular similarity in the ECFPs space showed a clear association with molecular taste and it was exploited for model development. Molecules laying in the subspaces where the taste assignation was more difficult were modeled trough a consensus between linear and local approaches (Partial Least Squares-Discriminant Analysis and N-nearest-neighbor classifier). The expert system, which was thoroughly validated through a Monte Carlo procedure and an external set, gave satisfactory results in comparison with the state-of-the-art models. Moreover, the QSTR model can be leveraged into a greater understanding of the relationship between molecular structure and sweetness, and into the design of novel sweeteners.

Research paper thumbnail of Similarity Coefficients for Binary Chemoinformatics Data: Overview and Extended Comparison Using Simulated and Real Data Sets

This paper reports an analysis and comparison of the use of 51 different similarity coefficients ... more This paper reports an analysis and comparison of the use of 51 different similarity coefficients for computing the similarities between binary fingerprints for both simulated and real chemical data sets. Five pairs and a triplet of coefficients were found to yield identical similarity values, leading to the elimination of seven of the coefficients. The remaining 44 coefficients were then compared in two ways: by their theoretical characteristics using simple descriptive statistics, correlation analysis, multidimensional scaling, Hasse diagrams, and the recently described atemporal target diffusion model; and by their effectiveness for similarity-based virtual screening using MDDR, WOMBAT, and MUV data. The comparisons demonstrate the general utility of the well-known Tanimoto method but also suggest other coefficients that may be worthy of further attention.

Research paper thumbnail of A new concept of higher-order similarity and the role of distance/ similarity measures in local classification methods

In this paper, a new concept of similarity is introduced with the aim of detecting higher-order s... more In this paper, a new concept of similarity is introduced with the aim of detecting higher-order similarities among objects, and meta-distances and meta-similarities are derived from it. A total of 100 meta-distances were obtained from a set of ten classical distances and were compared, in terms of classification performances, against classical distance measures. Classification methods based on local similarity analysis and several benchmark datasets were used. In several cases, the non-error rate (NER) of classifiers based on the new meta-distances significantly increased with respect to that of the classical Euclidean distance.

Research paper thumbnail of Quantitative structure–activity relationships to predict sweet and non‑sweet tastes

properly validated through cross-validation and external test sets. The applicability domain of m... more properly validated through cross-validation and external test sets. The applicability domain of models was investigated, and the interpretation of the role of the molecular descriptors in classifying sweet and non-sweet tastes was evaluated. The classification and the performance of the models presented in this paper are simple but accurate. They are based on a relatively small number of descriptors and a straightforward classification approach. The results presented here indicate that the proposed models can be used to accurately select new compounds as potential sweetener candidates.

Research paper thumbnail of QSAR study on the tropospheric degradation of organic compounds

Research paper thumbnail of Study of the POP atmospheric mobility by QSAR approach

Organohalogen Compounds, 1999

Research paper thumbnail of The BEAM-project: prediction and assessment of mixture toxicities in the aquatic environment

Continental Shelf Research, 2003

Freshwater and marine ecosystems are exposed to various multi-component mixtures of pollutants. N... more Freshwater and marine ecosystems are exposed to various multi-component mixtures of pollutants. Nevertheless, most ecotoxicological research and chemicals regulation focus on hazard and exposure assessment of individual substances only, the problem of chemical mixtures in the environment is ignored to a large extent. In contrast, the assessment of combination effects has a long tradition in pharmacology, where mixtures of chemicals are specifically designed to develop new products, e.g. human and veterinary drugs or agricultural and non-agricultural pesticides. In this area, two concepts are frequently used and are thought to describe fundamental relationships between single substance and mixture effects: Independent Action (Response Addition) and Concentration Addition. The question, to what extent these concepts may also be applied in an ecotoxicological and regulatory context may be considered a research topic of major importance, as the concepts would allow to make use of already existing single substance toxicity data for the predictive assessment of mixture toxicities. Two critical knowledge gaps are identified: (a) There is a lack of environmental realism, as a huge part of our current knowledge about the applicability of the concepts is restricted to artificial situations with respect to mixture composition or biological effect assessment. (b) The knowledge on what exactly is needed for using the concepts as tools for the predictive mixture toxicity assessment is insufficient. Both gaps seriously hamper the necessary, scientifically sound consideration of mixture toxicities in a regulatory context.

Research paper thumbnail of N3 and BNN: Two new similarity based classification methods in comparison with other classifiers

Two novel classification methods, called N3 (N-nearest neighbors) and BNN (binned nearest neighbo... more Two novel classification methods, called N3 (N-nearest neighbors) and BNN (binned nearest neighbors), are proposed. Both methods are inspired by the principles of the K-nearest neighbors (KNN) method, being both based on object pairwise similarities. Their performance was evaluated in comparison with nine well-known classification methods. In order to obtain reliable statistics, several comparisons were performed using 32 different literature data sets, which differ for number of objects, variables and classes. Results highlighted that N3 on average behaves as the most efficient classification method with similar performance to support vector machine based on radial basis function kernel (SVM/RBF). The method BNN showed on average higher performance than the classical K-nearest neighbors method.

Research paper thumbnail of BCF Dataset

Research paper thumbnail of Toxicity Data Daphnia

Research paper thumbnail of Generalizing the McClelland Bounds for Total π-Electron Energy

Zeitschrift für Naturforschung A, 2008

In 1971 McClelland obtained lower and upper bounds for the total π-electron energy. We now formul... more In 1971 McClelland obtained lower and upper bounds for the total π-electron energy. We now formulate the generalized version of these bounds, applicable to the energy-like expression

Research paper thumbnail of ATDM(Buscema-Todeschini- JCIM 2012)

This paper reports an analysis and comparison of the use of 51 different similarity coefficients ... more This paper reports an analysis and comparison of the use of 51 different similarity coefficients for computing the similarities between binary fingerprints for both simulated and real chemical data sets. Five pairs and a triplet of coefficients were found to yield identical similarity values, leading to the elimination of seven of the coefficients. The remaining 44 coefficients were then compared in two ways: by their theoretical characteristics using simple descriptive statistics, correlation analysis, multidimensional scaling, Hasse diagrams, and the recently described atemporal target diffusion model; and by their effectiveness for similarity-based virtual screening using MDDR, WOMBAT, and MUV data. The comparisons demonstrate the general utility of the well-known Tanimoto method but also suggest other coefficients that may be worthy of further attention.

Research paper thumbnail of A similarity-based QSAR model for predicting acute toxicity towards the fathead minnow (Pimephales promelas)

Research paper thumbnail of Assessing the validity of QSARs for ready biodegradability of chemicals: An Applicability Domain perspective

Research paper thumbnail of Chemometrics for QSAR Modeling

Comprehensive Chemometrics, 2020

Research paper thumbnail of Multivariate Classification for Qualitative Analysis

in Infrared Spectroscopy for Food Quality Analysis and Control, Da-Wen Sun (ED), Elsevier, 2008

Research paper thumbnail of Enhancing chemical information in QSAR: Generalized Graph-Theoretical Matrices

in Novel Molecular Structure Descriptors - Theory and Applications II, I. Gutman, B. Furtula (Eds.), University of Kragujevac and Faculty of Science Kragujevac, 2010

Research paper thumbnail of The DART (Decision Analysis by Ranking Techniques) software

in Scientific Data Ranking Methods: Theory and Applications, R. Todeschini, M. Pavan (EDs), Elsevier, 2008

Research paper thumbnail of Novel molecular descriptors based on functions of new vertex degrees

in Novel Molecular Structure Descriptors - Theory and Applications I, I. Gutman, B. Furtula (Eds.), University of Kragujevac and Faculty of Science Kragujevac, 2010