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), 1-13, 2019 | 42 | 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 | 36 | 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 | 16 | 2019 |
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 | 16 | 2012 |
Desarrollo de competencias y calidad universitaria P Martínez Clares, M Rubio, C Garvía, M Martínez Trabajo presentado en V Congreso Internacional de Galicia y Norte de …, 2003 | 15 | 2003 |
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 | 13 | 2018 |
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 | 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 | 9 | 2017 |
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 | 8 | 2019 |
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), 2019 | 8 | 2019 |
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 | 8 | 2010 |
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 | 7 | 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 | 5 | 2019 |
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 |
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 |
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 | 2 | 2022 |
PolyMaS: A new software to generate high molecular weight polymer macromolecules from repeating structural units SA Schustik, F Cravero, MJ Martinez, I Ponzoni, MF Diaz Polimery 66 (5), 293-297, 2021 | 2 | 2021 |
An integral framework for QSAR Modelling using Computational Intelligence and Visual Analytics F Cravero, G Vazquez, MJ Martínez, MF Díaz, I Ponzoni 6th Argentinian Conference on Bioinformatics and Computational Biology, 2015 | 1 | 2015 |