Emilio Benfenati

Alla P. Toropova, Andrey A. Toropov, A. Lombardo, Alessandra Roncaglioni, Emilio Benfenati, Giuseppina C. Gini: Coral: QSAR models for acute toxicity in fathead minnow (Pimephales promelas). Journal of Computational Chemistry 33(12): 1218-1223 (2012)

Andrey A. Toropov, Alla P. Toropova, Bakhtiyor F. Rasulev, Emilio Benfenati, Giuseppina C. Gini, Danuta Leszczynska, Jerzy Leszczynski: Coral: QSPR modeling of rate constants of reactions between organic aromatic pollutants and hydroxyl radical. Journal of Computational Chemistry 33(23): 1902-1906 (2012)

Natalja Fjodorova, Marjana Novic, Alessandra Roncaglioni, Emilio Benfenati: Evaluating the applicability domain in the case of classification predictive models for carcinogenicity based on the counter propagation artificial neural network. Journal of Computer-Aided Molecular Design 25(12): 1147-1158 (2011)

Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati, Giuseppina C. Gini, Danuta Leszczynska, Jerzy Leszczynski: CORAL: Quantitative structure-activity relationship models for estimating toxicity of organic compounds in rats. Journal of Computational Chemistry 32(12): 2727-2733 (2011)

Thomas Ferrari, Giuseppina C. Gini, Nazanin Golbamaki Bakhtyari, Emilio Benfenati: Mining toxicity structural alerts from SMILES: A new way to derive Structure Activity Relationships. CIDM 2011: 120-127

Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati, Danuta Leszczynska, Jerzy Leszczynski: SMILES-based optimal descriptors: QSAR analysis of fullerene-based HIV-1 PR inhibitors by means of balance of correlations. Journal of Computational Chemistry 31(2): 381-392 (2010)

Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati, Alberto Manganaro: QSPR modeling of enthalpies of formation for organometallic compounds by SMART-based optimal descriptors. Journal of Computational Chemistry 30(15): 2576-2582 (2009)

Andrey A. Toropov, Emilio Benfenati: SMILES as an alternative to the graph in QSAR modelling of bee toxicity. Computational Biology and Chemistry 31(1): 57-60 (2007)

Giuseppina C. Gini, Emilio Benfenati: E-Modelling: Foundations and Cases for Applying AI to Life Sciences. International Journal on Artificial Intelligence Tools 16(2): 243-268 (2007)

Frank Lemke, Emilio Benfenati, Johann-Adolf Müller: Data-driven modeling and prediction of acute toxicity of pesticide residues. SIGKDD Explorations 8(1): 71-79 (2006)

Uko Maran, Sulev Sild, Paolo Mazzatorta, Mosé Casalegno, Emilio Benfenati, Mathilde Romberg: Grid Computing for the Estimation of Toxicity: Acute Toxicity on Fathead Minnow (Pimephales promelas). GCCB 2006: 60-74

Tatiana I. Netzeva, Aynur O. Aptula, Emilio Benfenati, Mark T. D. Cronin, Giuseppina C. Gini, Iglika Lessigiarska, Uko Maran, Marjan Vracko, Gerrit Schüürmann: Description of the Electronic Structure of Organic Chemicals Using Semiempirical and Ab Initio Methods for Development of Toxicological QSARs. Journal of Chemical Information and Modeling 45(1): 106-114 (2005)

Martin Smiesko, Emilio Benfenati: Thermodynamic Descriptors Derived from Density Functional Theory Calculations in Prediction of Aquatic Toxicity. Journal of Chemical Information and Modeling 45(2): 379-385 (2005)

Filip Fratev, Emilio Benfenati: 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. Journal of Chemical Information and Modeling 45(3): 634-644 (2005)

Paolo Mazzatorta, Martin Smiesko, Elena Lo Piparo, Emilio Benfenati: QSAR Model for Predicting Pesticide Aquatic Toxicity. Journal of Chemical Information and Modeling 45(6): 1767-1774 (2005)

Sulev Sild, Uko Maran, Mathilde Romberg, Bernd Schuller, Emilio Benfenati: OpenMolGRID: Using Automated Workflows in GRID Computing Environment. EGC 2005: 464-473

Christoph König, Giuseppina C. Gini, Marian Viorel Craciun, Emilio Benfenati: Multiclass Classifier From A Combination Of Local Experts: Toward Distributed Computation For Real-Problem Classifiers. IJPRAI 18(5): 801-817 (2004)

Paolo Mazzatorta, Emilio Benfenati, Paola Lorenzini, Marco Vighi: QSAR in Ecotoxicity: An Overview of Modern Classification Techniques. Journal of Chemical Information and Modeling 44(1): 105-112 (2004)

Alessandra Roncaglioni, Marjana Novic, Marjan Vracko, Emilio Benfenati: Classification of Potential Endocrine Disrupters on the Basis of Molecular Structure Using a Nonlinear Modeling Method. Journal of Chemical Information and Modeling 44(2): 300-309 (2004)

Martin Smiesko, Emilio Benfenati: Predictive Models for Aquatic Toxicity of Aldehydes Designed for Various Model Chemistries. Journal of Chemical Information and Modeling 44(3): 976-984 (2004)

Giuseppina C. Gini, Marian Viorel Craciun, Christoph König, Emilio Benfenati: Combining Unsupervised and Supervised Artificial Neural Networks to PredictAquatic Toxicity. Journal of Chemical Information and Modeling 44(6): 1897-1902 (2004)

Frank Lemke, Johann-Adolf Müller, Emilio Benfenati: Modelling and Prediction of Toxicity of Environmental Pollutants. KELSI 2004: 221-234

Emilio Benfenati: Modelling Aquatic Toxicity with Advanced Computational Techniques: Procedures to Standardize Data and Compare Models. KELSI 2004: 235-248

Paolo Mazzatorta, Emilio Benfenati, Bernd Schuller, Mathilde Romberg, Damian McCourt, Werner Dubitzky, Sulev Sild, Mati Karelson, Ákos Papp, István Bágyi, Ferenc Darvas: OpenMolGRIND: Molecular Science and Engineering in a Grid Context. PDPTA 2004: 775-779

Jesús A. López, Emilio Benfenati, Werner Dubitzky (Eds.): Knowledge Exploration in Life Science Informatics, International Symposium,KELSI 2004, Milan, Italy, November 25-26, 2004, Proceedings. Lecture Notes in Computer Science 3303, Springer 2004, isbn 3-540-23927-8

Paolo Mazzatorta, Marjan Vracko, Emilio Benfenati: ANVAS: Artificial Neural Variables Adaptation System for descriptor selection. Journal of Computer-Aided Molecular Design 17(5-6): 335-346 (2003)

Paolo Mazzatorta, Marjan Vracko, Aneta Jezierska, Emilio Benfenati: Modeling Toxicity by Using Supervised Kohonen Neural Networks. Journal of Chemical Information and Computer Sciences 43(2): 485-492 (2003)

Paolo Mazzatorta, Emilio Benfenati, Ciprian-Daniel Neagu, Giuseppina C. Gini: Tuning Neural and Fuzzy-Neural Networks for Toxicity Modeling. Journal of Chemical Information and Computer Sciences 43(2): 513-518 (2003)

Damian McCourt, Jesús A. López, Emilio Benfenati, Paolo Mazzatorta, Mathilde Romberg, Bernd Schuller, Werner Dubitzky: Towards and Intelligent Data Type for Toxicity. IC-AI 2003: 328-334

Paolo Mazzatorta, Emilio Benfenati, Daniel Neagu, Giuseppina C. Gini: The Importance of Scaling in Data Mining for Toxicity Prediction. Journal of Chemical Information and Computer Sciences 42(5): 1250-1255 (2002)

Ciprian-Daniel Neagu, Emilio Benfenati, Giuseppina C. Gini, Paolo Mazzatorta, Alessandra Roncaglioni: Neuro-Fuzzy Knowledge Representation for Toxicity Prediction of Organic Compounds. ECAI 2002: 498-502

Emilio Benfenati, Paolo Mazzatorta, Daniel Neagu, Giuseppina C. Gini: Combining Classifiers of Pesticides Toxicity through a Neuro-fuzzy Approach. Multiple Classifier Systems 2002: 293-303

Giuseppina C. Gini, Emilio Benfenati: Results from a Data Mining Approach to Predictive Toxicology. The Case of Pesticides Data. PRIS 2002: 114-123

Alan R. Katritzky, Ruslan Petrukhin, Douglas B. Tatham, Subhash C. Basak, Emilio Benfenati, Mati Karelson, Uko Maran: Interpretation of Quantitative Structure-Property and -Activity Relationships. Journal of Chemical Information and Computer Sciences 41(3): 679-685 (2001)

Giuseppina C. Gini, Marco Lorenzini, Emilio Benfenati, Raffaella Brambilla, Luca Malvé: Mixing a Symbolic and a Subsymbolic Expert to Improve Carcinogenicity Prediction of Aromatic Compounds. Multiple Classifier Systems 2001: 126-135

Giuseppina C. Gini, Emilio Benfenati, Daniel Boley: Clustering and classification techniques to assess aquatic toxicity. KES 2000: 166-172

Giuseppina C. Gini, Marco Lorenzini, Emilio Benfenati, Paola Grasso, Maurizio Bruschi: Predictive Carcinogenicity: A Model for Aromatic Compounds, with Nitrogen-Containing Substituents, Based on Molecular Descriptors Using an Artificial Neural Network. Journal of Chemical Information and Computer Sciences 39(6): 1076-1080 (1999)

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