Domenico Gadaleta

发表

Adverse outcome pathways: opportunities, limitations and open questions

S. H. Bennekou, F. Oesch, S. Dooley, 2017, Archives of Toxicology.

Applicability Domain for QSAR models: where theory meets reality

G. Mangiatordi, O. Nicolotti, Domenico Gadaleta, 2016 .

Zebrafish AC50 modelling: (Q)SAR models to predict developmental toxicity in zebrafish embryo.

E. Benfenati, A. Toropova, A. Toropov, 2020, Ecotoxicology and environmental safety.

Integrating computational methods to predict mutagenicity of aromatic azo compounds

Emilio Benfenati, Alberto Manganaro, Serena Manganelli, 2017, Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews.

A knowledge-based expert rule system for predicting mutagenicity (Ames test) of aromatic amines and azo compounds.

E. Benfenati, A. Manganaro, Domenico Gadaleta, 2016, Toxicology.

REACH and in silico methods: an attractive opportunity for medicinal chemists.

Emilio Benfenati, Angelo Carotti, Ettore Novellino, 2014, Drug discovery today.

Identification of structural alerts for liver and kidney toxicity using repeated dose toxicity data

Emilio Benfenati, Anna Lombardo, Orazio Nicolotti, 2015, Chemistry Central Journal.

QSAR Development for Plasma Protein Binding: Influence of the Ionization State

E. Benfenati, A. Toropova, A. Toropov, 2018, Pharmaceutical Research.

New in silico models to predict in vitro micronucleus induction as marker of genotoxicity.

E. Benfenati, D. Baderna, A. Lombardo, 2019, Journal of hazardous materials.

In silico design of novel 2H-chromen-2-one derivatives as potent and selective MAO-B inhibitors.

Angelo Carotti, Orazio Nicolotti, Domenico Gadaleta, 2015, European journal of medicinal chemistry.

A rational approach to elucidate human monoamine oxidase molecular selectivity

G. Lattanzi, D. Alberga, G. Mangiatordi, 2017, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

Structure-Based Design and Optimization of Multitarget-Directed 2H-Chromen-2-one Derivatives as Potent Inhibitors of Monoamine Oxidase B and Cholinesterases.

P. Carrupt, Alessandra Nurisso, N. Denora, 2015, Journal of medicinal chemistry.

Automated Integration of Structural, Biological and Metabolic Similarities to Sustain Read-Across.

Emilio Benfenati, Alessandra Roncaglioni, Domenico Gadaleta, 2020, ALTEX.

The role of ‘big data’ and ‘in silico’ New Approach Methodologies (NAMs) in ending animal use – a commentary on progress

Timothy E. H. Allen, Domenico Gadaleta, R. Ram, 2022, Computational Toxicology.

Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity

E. Benfenati, A. Toropova, A. Toropov, 2022, International journal of molecular sciences.

QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors

E. Benfenati, N. Kramer, D. Baderna, 2020, Molecules.

Novel chemotypes targeting tubulin at the colchicine binding site and unbiasing P-glycoprotein.

R. Iacobazzi, N. Denora, D. Alberga, 2017, European journal of medicinal chemistry.

A K-nn Algorithm for Predicting the Oral Sub- Chronic Toxicity in the Rat

Emilio Benfenati, Angelo Carotti, Anna Lombardo, 2022 .

Ligand-based prediction of hERG-mediated cardiotoxicity based on the integration of different machine learning techniques

E. Benfenati, M. Saviano, G. Mangiatordi, 2022, Frontiers in Pharmacology.

Automated Integration of Structural, Biological and Metabolic Similarities to Improve Read-Across

Azadi Golbamaki Bakhtyari, E. Benfenati, Domenico Gadaleta, 2020 .

Fine molecular tuning at position 4 of 2H-chromen-2-one derivatives in the search of potent and selective monoamine oxidase B inhibitors.

O. Nicolotti, Domenico Gadaleta, M. Catto, 2013, European journal of medicinal chemistry.

SAR and QSAR modeling of a large collection of LD50 rat acute oral toxicity data

Emilio Benfenati, Giovanna J. Lavado, Alessandra Roncaglioni, 2019, Journal of Cheminformatics.

Integrated in silico models for the prediction of No-Observed-(Adverse)-Effect-Levels and Lowest-Observed-(Adverse)-Effect-Levels in rats for sub-chronic repeated dose toxicity.

E. Benfenati, J. Dorne, A. Toropova, 2020, Chemical research in toxicology.

Developing innovative in silico models with EFSA's OpenFoodTox database

Emilio Benfenati, Andrey A. Toropov, Alla P. Toropova, 2017 .

CATMoS: Collaborative Acute Toxicity Modeling Suite

Kimberley M. Zorn, Daniel P. Russo, Timothy E. H. Allen, 2021, Environmental health perspectives.

Prediction of the Neurotoxic Potential of Chemicals Based on Modelling of Molecular Initiating Events Upstream of the Adverse Outcome Pathways of (Developmental) Neurotoxicity

M. Cronin, E. Benfenati, Domenico Gadaleta, 2022, International journal of molecular sciences.

Evaluation and comparison of benchmark QSAR models to predict a relevant REACH endpoint: The bioconcentration factor (BCF).

Emilio Benfenati, Anna Lombardo, Alessandra Roncaglioni, 2015, Environmental research.

Ecotoxicological QSAR modeling of the acute toxicity of organic compounds to the freshwater crustacean Thamnocephalus platyurus.

E. Benfenati, K. Roy, D. Baderna, 2021, Chemosphere.

Mind the Gap! A Journey towards Computational Toxicology

Angelo Carotti, Saverio Cellamare, Daniela Trisciuzzi, 2016, Molecular informatics.

A descriptor-based analysis to highlight the mechanistic rationale of mutagenicity

E. Benfenati, Domenico Gadaleta, 2021, Journal of environmental science and health. Part C, Toxicology and carcinogenesis.

A KNIME Workflow to Assist the Analogue Identification for Read-Across, Applied to Aromatase Activity

E. Benfenati, Domenico Gadaleta, A. Roncaglioni, 2023, Molecules.

Quantitative Structure-Activity Relationship Modeling of the Amplex Ultrared Assay to Predict Thyroperoxidase Inhibitory Activity

E. Benfenati, Domenico Gadaleta, A. Roncaglioni, 2021, Frontiers in Pharmacology.

QSAR Modeling of ToxCast Assays Relevant to the Molecular Initiating Events of AOPs Leading to Hepatic Steatosis

Emilio Benfenati, Enrico Mombelli, Serena Manganelli, 2018, J. Chem. Inf. Model..

A read-across case study on chronic toxicity of branched carboxylic acids (1): Integration of mechanistic evidence from new approach methodologies (NAMs) to explore a common mode of action.

Thomas E. Exner, E. Benfenati, O. Taboureau, 2021, Toxicology in Vitro.

An alternative QSAR-based approach for predicting the bioconcentration factor for regulatory purposes.

Emilio Benfenati, Angelo Carotti, Matteo Floris, 2014, ALTEX.

Integration of QSAR models for bioconcentration suitable for REACH.

Emilio Benfenati, Anna Lombardo, Angelo Carotti, 2013, The Science of the total environment.

CORAL: model for no observed adverse effect level (NOAEL)

E. Benfenati, A. Toropova, A. Toropov, 2015, Molecular Diversity.

In Silico Models for Repeated-Dose Toxicity (RDT): Prediction of the No Observed Adverse Effect Level (NOAEL) and Lowest Observed Adverse Effect Level (LOAEL) for Drugs.

E. Benfenati, Domenico Gadaleta, F. Pizzo, 2022, Methods in molecular biology.

Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite

Stephen P. Boyd, Kimberley M. Zorn, Daniel P. Russo, 2021, Environmental health perspectives.

Collaborative SAR Modeling and Prospective In Vitro Validation of Oxidative Stress Activation in Human HepG2 Cells

J. C. Gómez-Tamayo, G. V. van Westen, U. Norinder, 2023, Journal of Chemical Information and Modeling.

A new semi-automated workflow for chemical data retrieval and quality checking for modeling applications

Emilio Benfenati, Cosimo Toma, Domenico Gadaleta, 2018, Journal of Cheminformatics.

A k-NN algorithm for predicting the oral sub-chronic toxicity in the rat.

E. Benfenati, O. Nicolotti, A. Lombardo, 2014, ALTEX.

Systematic evaluation of high-throughput PBK modelling strategies for the prediction of intravenous and oral pharmacokinetics in humans

Domenico Gadaleta, Erika Colombo, Eva Serrano-Candelas, 2024, bioRxiv.

Methodology of aiQSAR: a group-specific approach to QSAR modelling

Emilio Benfenati, Domenico Gadaleta, Kristijan Vukovic, 2019, Journal of Cheminformatics.