| QSAR classification models for predicting the activity of inhibitors of beta-secretase (BACE1) associated with Alzheimer’s disease I Ponzoni, V Sebastián-Pérez, MJ Martínez, C Roca, C De la Cruz Pérez, ... Scientific reports 9 (1), 9102, 2019 | 54 | 2019 |
| Visual analytics in cheminformatics: user-supervised descriptor selection for QSAR methods MJ Martínez, I Ponzoni, MF Díaz, GE Vazquez, AJ Soto Journal of cheminformatics 7, 1-17, 2015 | 39 | 2015 |
| Modesus: A machine learning tool for selection of molecular descriptors in qsar studies applied to molecular informatics MJ Martínez, M Razuc, I Ponzoni BioMed research international 2019, 2019 | 22 | 2019 |
| Biclustering as strategy for improving feature selection in consensus QSAR modeling MJ Martínez, JS Dussaut, I Ponzoni Electronic Notes in Discrete Mathematics 69, 117-124, 2018 | 17 | 2018 |
| QSPR Models for Predicting Log Pliver Values for Volatile Organic Compounds Combining Statistical Methods and Domain Knowledge D Palomba, MJ Martínez, I Ponzoni, MF Díaz, GE Vazquez, AJ Soto Molecules 17 (12), 14937-14953, 2012 | 17 | 2012 |
| QSAR modelling to identify LRRK2 inhibitors for Parkinson’s disease V Sebastián-Pérez, MJ Martínez, C Gil, NE Campillo, A Martínez, ... Journal of integrative bioinformatics 16 (1), 20180063, 2019 | 14 | 2019 |
| Feature Selection for Polymer Informatics: Evaluating Scalability and Robustness of the FS4RVDD Algorithm Using Synthetic Polydisperse Data Sets F Cravero, SA Schustik, MJ Martínez, GE Vázquez, MF Díaz, I Ponzoni Journal of chemical information and modeling 60 (2), 592-603, 2019 | 12 | 2019 |
| Computer-aided design of polymeric materials: Computational study for characterization of databases for prediction of mechanical properties under polydispersity F Cravero, SA Schustik, MJ Martínez, CD Barranco, MF Díaz, I Ponzoni Chemometrics and Intelligent Laboratory Systems 191, 65-72, 2019 | 12 | 2019 |
| Computational modelling of mechanical properties for new polymeric materials with high molecular weight F Cravero, MJ Martínez, I Ponzoni, MF Diaz Chemometrics and Intelligent Laboratory Systems 193, 103851, 2019 | 11 | 2019 |
| GeRNet: a gene regulatory network tool JS Dussaut, CA Gallo, F Cravero, MJ Martínez, JA Carballido, I Ponzoni Biosystems 162, 1-11, 2017 | 11 | 2017 |
| Comparación de las características fisiológicas del patinaje de velocidad sobre ruedas con el cicloergómetro y el tapiz rodante. Centro de Investigación y Medicina del Deporte … M Martínez Revista de Investigación y Documentación sobre las ciencias de la Educación …, 1991 | 9 | 1991 |
| DELPHOS: computational tool for selection of relevant descriptor subsets in ADMET prediction AJ Soto, MJ Martínez, RL Cecchini, GE Vazquez, I Ponzoni 1st International Meeting of Pharmaceutical Sciences, 2010 | 7 | 2010 |
| QSAR Classification models for predicting the activity of inhibitors of beta-secretase (BACE1) associated with Alzheimer’s disease. Sci Rep 9: 9102 I Ponzoni, V Sebastián-Pérez, MJ Martínez, C Roca, C De la Cruz Pérez, ... | 6 | 2019 |
| Feature selection and polydispersity characterization for QSPR modelling: predicting a tensile property F Cravero, S Schustik, MJ Martínez, CD Barranco, MF Díaz, I Ponzoni Practical Applications of Computational Biology and Bioinformatics, 12th …, 2019 | 6 | 2019 |
| Multitask Deep Neural Networks for Ames Mutagenicity Prediction MJ Martínez, MV Sabando, AJ Soto, C Roca, C Requena-Triguero, ... Journal of Chemical Information and Modeling 62 (24), 6342-6351, 2022 | 5 | 2022 |
| FS4RVDD: A Feature Selection Algorithm for Random Variables with Discrete Distribution F Cravero, S Schustik, MJ Martínez, MF Díaz, I Ponzoni Information Processing and Management of Uncertainty in Knowledge-Based …, 2018 | 5 | 2018 |
| Qsar classification models for predicting affinity to blood or liver of volatile organic compounds in e-health F Cravero, MJ Martínez, MF Díaz, I Ponzoni Bioinformatics and Biomedical Engineering: 5th International Work-Conference …, 2017 | 4 | 2017 |
| Design of new dispersants using machine learning and visual analytics MJ Martínez, R Naveiro, AJ Soto, P Talavante, SH Kim Lee, ... Polymers 15 (5), 1324, 2023 | 3 | 2023 |
| QSAR modelling for drug discovery: predicting the activity of LRRK2 inhibitors for parkinson’s disease using cheminformatics approaches V Sebastián-Pérez, MJ Martínez, C Gil, NE Campillo, A Martínez, ... Practical Applications of Computational Biology and Bioinformatics, 12th …, 2019 | 3 | 2019 |
| Intelligent Systems for Predictive Modelling in Cheminformatics: QSPR Models for Material Design using Machine Learning and Visual Analytics Tools F Cravero, MJ Martinez, GE Vazquez, MF Díaz, I Ponzoni 10th International Conference on Practical Applications of Computational …, 2016 | 3 | 2016 |
Ignacio PonzoniPrincipal Researcher at CONICET - Associated Professor at Universidad Nacional del SurE-mailová adresa ověřena na: cs.uns.edu.ar
