Predictive Toxicology Results Integrating Different AI Paradigms: The Carcinogenicity Case. - Giuseppina C. Gini; Emilio Benfenati; Paola Grasso; Marco Lorenzini (IIA/SOCO, 1999)

Predictive Carcinogenicity: A Model for Aromatic Compounds, with Nitrogen-Containing Substituents, Based on Molecular Descriptors Using an Artificial Neural Network. - Giuseppina C. Gini; Marco Lorenzini; Emilio Benfenati; Paola Grasso; Maurizio Bruschi (J. Chem. Inf. Comput. Sci., 1999)

Clustering and classification techniques to assess aquatic toxicity. - Giuseppina C. Gini; Emilio Benfenati; Daniel Boley (KES, 2000)

Mixing a Symbolic and a Subsymbolic Expert to Improve Carcinogenicity Prediction of Aromatic Compounds. - Giuseppina C. Gini; Marco Lorenzini; Emilio Benfenati; Raffaella Brambilla; Luca Malvé (Multiple Classifier Systems, 2001)

Interpretation of Quantitative Structure-Property and -Activity Relationships. - Alan R. Katritzky; Ruslan Petrukhin; Douglas B. Tatham; Subhash C. Basak; Emilio Benfenati; Mati Karelson; Uko Maran (J. Chem. Inf. Comput. Sci., 2001)

Neuro-Fuzzy Knowledge Representation for Toxicity Prediction of Organic Compounds. - Ciprian-Daniel Neagu; Emilio Benfenati; Giuseppina C. Gini; Paolo Mazzatorta; Alessandra Roncaglioni (ECAI, 2002)

Combining Classifiers of Pesticides Toxicity through a Neuro-fuzzy Approach. - Emilio Benfenati; Paolo Mazzatorta; Daniel Neagu; Giuseppina C. Gini (Multiple Classifier Systems, 2002)

Results from a Data Mining Approach to Predictive Toxicology. The Case of Pesticides Data. - Giuseppina C. Gini; Emilio Benfenati (PRIS, 2002)

The Importance of Scaling in Data Mining for Toxicity Prediction. - Paolo Mazzatorta; Emilio Benfenati; Daniel Neagu; Giuseppina C. Gini (J. Chem. Inf. Comput. Sci., 2002)

Towards and Intelligent Data Type for Toxicity. - Damian McCourt; Jesús A. López; Emilio Benfenati; Paolo Mazzatorta; Mathilde Romberg; Bernd Schuller; Werner Dubitzky (IC-AI, 2003)

ANVAS: Artificial Neural Variables Adaptation System for descriptor selection. - Paolo Mazzatorta; Marjan Vracko; Emilio Benfenati (J. Comput. Aided Mol. Des., 2003)

Tuning Neural and Fuzzy-Neural Networks for Toxicity Modeling. - Paolo Mazzatorta; Emilio Benfenati; Ciprian-Daniel Neagu; Giuseppina C. Gini (J. Chem. Inf. Comput. Sci., 2003)

Modeling Toxicity by Using Supervised Kohonen Neural Networks. - Paolo Mazzatorta; Marjan Vracko; Aneta Jezierska; Emilio Benfenati (J. Chem. Inf. Comput. Sci., 2003)

Modelling Aquatic Toxicity with Advanced Computational Techniques: Procedures to Standardize Data and Compare Models. - Emilio Benfenati (KELSI, 2004)

Modelling and Prediction of Toxicity of Environmental Pollutants. - Frank Lemke; Johann-Adolf Müller; Emilio Benfenati (KELSI, 2004)

OpenMolGRIND: Molecular Science and Engineering in a Grid Context. - Paolo Mazzatorta; Emilio Benfenati; Bernd Schuller; Mathilde Romberg; Damian McCourt; Werner Dubitzky; Sulev Sild; Mati Karelson; Ákos Papp; István Bágyi; Ferenc Darvas (PDPTA, 2004)

Multiclass Classifier From A Combination Of Local Experts: Toward Distributed Computation For Real-Problem Classifiers. - Christoph König 004; Giuseppina C. Gini; Marian Viorel Craciun; Emilio Benfenati (Int. J. Pattern Recognit. Artif. Intell., 2004)

Combining Unsupervised and Supervised Artificial Neural Networks to PredictAquatic Toxicity. - Giuseppina C. Gini; Marian Viorel Craciun; Christoph König 004; Emilio Benfenati (J. Chem. Inf. Model., 2004)

QSAR in Ecotoxicity: An Overview of Modern Classification Techniques. - Paolo Mazzatorta; Emilio Benfenati; Paola Lorenzini; Marco Vighi (J. Chem. Inf. Model., 2004)

Classification of Potential Endocrine Disrupters on the Basis of Molecular Structure Using a Nonlinear Modeling Method. - Alessandra Roncaglioni; Marjana Novic; Marjan Vracko; Emilio Benfenati (J. Chem. Inf. Model., 2004)

Predictive Models for Aquatic Toxicity of Aldehydes Designed for Various Model Chemistries. - Martin Smiesko; Emilio Benfenati (J. Chem. Inf. Model., 2004)

OpenMolGRID: Using Automated Workflows in GRID Computing Environment. - Sulev Sild; Uko Maran; Mathilde Romberg; Bernd Schuller; Emilio Benfenati (EGC, 2005)

3D-QSAR and Molecular Mechanics Study for the Differences in the Azole Activity against Yeastlike and Filamentous Fungi and Their Relation to P450DM Inhibition. 1. 3-Substituted-4(3H)-quinazolinones. - Filip Fratev; Emilio Benfenati (J. Chem. Inf. Model., 2005)

QSAR Model for Predicting Pesticide Aquatic Toxicity. - Paolo Mazzatorta; Martin Smiesko; Elena Lo Piparo; Emilio Benfenati (J. Chem. Inf. Model., 2005)

Description of the Electronic Structure of Organic Chemicals Using Semiempirical and Ab Initio Methods for Development of Toxicological QSARs. - Tatiana I. Netzeva; Aynur O. Aptula; Emilio Benfenati; Mark T. D. Cronin; Giuseppina C. Gini; Iglika Lessigiarska; Uko Maran; Marjan Vracko; Gerrit Schüürmann (J. Chem. Inf. Model., 2005)

Thermodynamic Descriptors Derived from Density Functional Theory Calculations in Prediction of Aquatic Toxicity. - Martin Smiesko; Emilio Benfenati (J. Chem. Inf. Model., 2005)

Grid Computing for the Estimation of Toxicity: Acute Toxicity on Fathead Minnow (Pimephales promelas). - Uko Maran; Sulev Sild; Paolo Mazzatorta; Mosé Casalegno; Emilio Benfenati; Mathilde Romberg (GCCB, 2006)

Data-driven modeling and prediction of acute toxicity of pesticide residues. - Frank Lemke; Emilio Benfenati; Johann-Adolf Müller (SIGKDD Explor., 2006)

Open Computing Grid for Molecular Sciences. - Mathilde Romberg; Emilio Benfenati; Werner Dubitzky (Grid Computing for Bioinformatics and Computational Biology, 2007)

SMILES as an alternative to the graph in QSAR modelling of bee toxicity. - Andrey A. Toropov; Emilio Benfenati (Comput. Biol. Chem., 2007)

E-Modelling: Foundations and Cases for Applying AI to Life Sciences. - Giuseppina C. Gini; Emilio Benfenati (Int. J. Artif. Intell. Tools, 2007)

Definition and Detection of Outliers in Chemical Space. - Mosé Casalegno; Guido Sello; Emilio Benfenati (J. Chem. Inf. Model., 2008)

QSPR modeling of enthalpies of formation for organometallic compounds by SMART-based optimal descriptors. - Andrey A. Toropov; Alla P. Toropova; Emilio Benfenati; Alberto Manganaro (J. Comput. Chem., 2009)

SMILES-based optimal descriptors: QSAR analysis of fullerene-based HIV-1 PR inhibitors by means of balance of correlations. - Andrey A. Toropov; Alla P. Toropova; Emilio Benfenati; Danuta Leszczynska; Jerzy Leszczynski (J. Comput. Chem., 2010)

Mining toxicity structural alerts from SMILES: A new way to derive Structure Activity Relationships. - Thomas Ferrari; Giuseppina C. Gini; Nazanin Golbamaki Bakhtyari; Emilio Benfenati (CIDM, 2011)

Evaluating the applicability domain in the case of classification predictive models for carcinogenicity based on the counter propagation artificial neural network. - Natalja Fjodorova; Marjana Novic; Alessandra Roncaglioni; Emilio Benfenati (J. Comput. Aided Mol. Des., 2011)

CORAL: Quantitative structure-activity relationship models for estimating toxicity of organic compounds in rats. - Alla P. Toropova; Andrey A. Toropov; Emilio Benfenati; Giuseppina C. Gini; Danuta Leszczynska; Jerzy Leszczynski (J. Comput. Chem., 2011)

Identification of Toxifying and Detoxifying Moieties for Mutagenicity Prediction by Priority Assessment. - Mosé Casalegno; Emilio Benfenati; Guido Sello (J. Chem. Inf. Model., 2011)

Coral: QSPR modeling of rate constants of reactions between organic aromatic pollutants and hydroxyl radical. - Andrey A. Toropov; Alla P. Toropova; Bakhtiyor F. Rasulev; Emilio Benfenati; Giuseppina C. Gini; Danuta Leszczynska; Jerzy Leszczynski (J. Comput. Chem., 2012)

Coral: QSAR models for acute toxicity in fathead minnow (Pimephales promelas). - Alla P. Toropova; Andrey A. Toropov; Anna Lombardo; Alessandra Roncaglioni; Emilio Benfenati; Giuseppina C. Gini (J. Comput. Chem., 2012)

VEGA-QSAR: AI Inside a Platform for Predictive Toxicology. - Emilio Benfenati; Alberto Manganaro; Giuseppina C. Gini (PAI@AI*IA, 2013)

A generalizable definition of chemical similarity for read-across. - Matteo Floris; Alberto Manganaro; Orazio Nicolotti; Ricardo Medda; Giuseppe Felice Mangiatordi; Emilio Benfenati (J. Cheminformatics, 2014)

Prediction of antimicrobial activity of large pool of peptides using quasi-SMILES. - Alla P. Toropova; Andrey A. Toropov; Emilio Benfenati; Danuta Leszczynska; Jerzy Leszczynski (Biosyst., 2018)

A new semi-automated workflow for chemical data retrieval and quality checking for modeling applications. - Domenico Gadaleta; Anna Lombardo; Cosimo Toma; Emilio Benfenati (J. Cheminformatics, 2018)

QSAR Modeling of ToxCast Assays Relevant to the Molecular Initiating Events of AOPs Leading to Hepatic Steatosis. - Domenico Gadaleta; Serena Manganelli; Alessandra Roncaglioni; Cosimo Toma; Emilio Benfenati; Enrico Mombelli (J. Chem. Inf. Model., 2018)

Correction to: A new semi-automated workflow for chemical data retrieval and quality checking for modeling applications. - Domenico Gadaleta; Anna Lombardo; Cosimo Toma; Emilio Benfenati (J. Cheminformatics, 2019)

SAR and QSAR modeling of a large collection of LD50 rat acute oral toxicity data. - Domenico Gadaleta; Kristijan Vukovic; Cosimo Toma; Giovanna J. Lavado; Agnes L. Karmaus; Kamel Mansouri; Nicole C. Kleinstreuer; Emilio Benfenati; Alessandra Roncaglioni (J. Cheminformatics, 2019)

Methodology of aiQSAR: a group-specific approach to QSAR modelling. - Kristijan Vukovic; Domenico Gadaleta; Emilio Benfenati (J. Cheminformatics, 2019)

The index of ideality of correlation improves the predictive potential of models of the antioxidant activity of tripeptides from frog skin (Litoria rubella). - Alla P. Toropova; Andrey A. Toropov; Alessandra Roncaglioni; Emilio Benfenati (Comput. Biol. Medicine, 2021)

Quantitative structure-activity relationships of chemical bioactivity toward proteins associated with molecular initiating events of organ-specific toxicity. - Domenico Gadaleta; Marina Garcia de Lomana; Eva Serrano-Candelas; Rita Ortega-Vallbona; Rafael Gozalbes; Alessandra Roncaglioni; Emilio Benfenati (J. Cheminformatics, 2024)

Comprehensive benchmarking of computational tools for predicting toxicokinetic and physicochemical properties of chemicals. - Domenico Gadaleta; Eva Serrano-Candelas; Rita Ortega-Vallbona; Erika Colombo; Marina Garcia de Lomana; Giada Biava; Pablo Aparicio-Sánchez; Alessandra Roncaglioni; Rafael Gozalbes; Emilio Benfenati (J. Cheminformatics, 2024)

Simulation peptide toxicity using the fragments of local symmetry in amino acid sequences. - Andrey A. Toropov; Alla P. Toropova; Valentin O. Kudyshkin; Emilio Benfenati; Danuta Leszczynska; Jerzy Leszczynski (Biosyst., 2025)

Comparison of Optimised Geometric Deep Learning Architectures, over Varying Toxicological Assay Data Environments. - Alexander D. Kalian; Lennart Otte; Jaewook Lee; Emilio Benfenati; Jean-Lou C. M. Dorne; Claire Potter; Olivia J. Osborne; Miao Guo; Christer Hogstrand (CoRR, 2025)