Fiorella Cravero
Fiorella Cravero
Becaria Postdoctoral, Instituto Ciencias e ingeniería de la Computacion (ICIC), UNS-CONICET
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Hybridizing feature selection and feature learning approaches in QSAR modeling for drug discovery
I Ponzoni, V Sebastián-Pérez, C Requena-Triguero, C Roca, MJ Martínez, ...
Scientific reports 7 (1), 1-19, 2017
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
Feature learning applied to the estimation of tensile strength at break in polymeric material design
C Fiorella, MM Jimena, V Gustavo, MF Díaz, P Ignacio
Journal of integrative bioinformatics 13 (2), 15-29, 2016
Polymer informatics: Expert-in-the-loop in QSPR modeling of refractive index
SA Schustik, F Cravero, I Ponzoni, MF Díaz
Computational Materials Science 194, 110460, 2021
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
Gernet: a gene regulatory network tool
JS Dussaut, CA Gallo, F Cravero, MJ Martínez, JA Carballido, I Ponzoni
Biosystems 162, 1-11, 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
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
Highlights of the 1st Argentine Symposium of Young Bioinformatics Researchers (1SAJIB) organized by the ISCB RSG-Argentina
RG Parra, LA Defelipe, AB Guzovsky, A Monzón, F Cravero, E Mancini, ...
PeerJ, 2016
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
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
Second iscb latin american student council symposium (la-scs) 2016
AM Monzon, MA Hasenahuer, E Mancini, N Coimbra, F Cravero, ...
F1000Research 6, 2017
2nd Argentine Symposium of Young Bioinformatics Researchers (2SAJIB) organized by the ISCB-SC RSG-Argentina
F Cravero, LU Landaburu, NN Moreyra, E Fenoy, CLP Franzotti, ...
PeerJ Preprints, 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
Modelado QSPR de propiedades mecánicas de materiales poliméricos empleando técnicas de reducción de variables basadas en algoritmos de aprendizaje automático (in Spanish). CAIQ
F Cravero, GE Vazquez, MF Diaz, I Ponzoni
Proceeding of the Conference of Chemical Engineering. Buenos Aires, Argentina, 2015
Prediction of tensile strength at break for linear polymers applied to new materials development
D Palomba, F Cravero, GE Vazquez, MF Diaz
Proceeding of the International Congress of Metallurgy and Materials-Sam …, 2014
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
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
How can polydispersity information be integrated in the QSPR modeling of mechanical properties?
F Cravero, SA Schustik, MJ Martínez, MF Diaz, I Ponzoni
Science and Technology of Advanced Materials: Methods 2 (1), 1-13, 2022
Polymer informatics for QSPR prediction of tensile mechanical properties. Case study: Strength at break
F Cravero, MF Díaz, I Ponzoni
The Journal of Chemical Physics 156 (20), 204903, 2022
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