Knowledge Component of a Multiagent Distributed Decision Support System. - Georgina Stegmayer; María Laura Caliusco; Omar Chiotti; María Rosa Galli (CLEI Electron. J., 2002)

Volterra series and neural networks to model an electronic device nonlinear behavior. - Georgina Stegmayer (IJCNN, 2004)

A Neural Network that helps building a Nonlinear Dynamical model of a Power Amplifier. - Georgina Stegmayer; Omar Chiotti; Giancarlo Orengo (ESANN, 2005)

Comparison of Volterra Models Extracted from a Neural Network for Nonlinear Systems Modeling. - Georgina Stegmayer (ICANN (2), 2005)

Identification of Frequency-Domain Volterra Model Using Neural Networks. - Georgina Stegmayer; Omar Chiotti (ICANN (2), 2005)

Novel Neural Network application to nonlinear electronic devices: building a Volterra series model. - Georgina Stegmayer; Omar Chiotti (Inteligencia Artif., 2005)

Neural Networks applied to wireless communications. - Georgina Stegmayer; Omar Chiotti (IFIP AI, 2006)

Neural Networks and Volterra series for modeling new wireless communication devices. - Georgina Stegmayer (IJCNN, 2007)

ANN-Agent for Distributed Knowledge Source Discovery. - Georgina Stegmayer; María Laura Caliusco; Omar Chiotti; María Rosa Galli (OTM Workshops (1), 2007)

Estimation of the Particle Size Distribution of a Latex using a General Regression Neural Network. - Georgina Stegmayer; Jorge R. Vega; Luis M. Gugliotta; Omar Chiotti (IFIP AI, 2008)

Artificial Life Contest - A Tool for Informal Teaching of Artificial Intelligence. - Diego H. Milone; Georgina Stegmayer; Daniel Beber (CSEDU (1), 2009)

Neural network model for integration and visualization of introgressed genome and metabolite data. - Georgina Stegmayer; Diego H. Milone; Laura Kamenetzky; Mariana G. Lopez; Fernando Carrari (IJCNN, 2009)

Knowledge Source Discovery: An Experience Using Ontologies, WordNet and Artificial Neural Networks. - Mariano Rubiolo; María Laura Caliusco; Georgina Stegmayer; Matías Gareli; Mauricio Coronel (KES (2), 2009)

Array of Multilayer Perceptrons with No-class Resampling Training for Face Recognition. - D. Capello; César Ernesto Martínez; Diego H. Milone; Georgina Stegmayer (Inteligencia Artif., 2009)

Métodos de agrupamiento no supervisado para la integración de datos genómicos y metabólicos de múltiples líneas de introgresión. - Diego H. Milone; Georgina Stegmayer; Matias Gerard; Laura Kamenetzky; Mariana G. Lopez; Fernando Carrari (Inteligencia Artif., 2009)

Volterra NN-based behavioral model for new wireless communications devices. - Georgina Stegmayer; Omar Chiotti (Neural Comput. Appl., 2009)

Compressing a neural network classifier using a Volterra-Neural Network model. - Mariano Rubiolo; Georgina Stegmayer; Diego H. Milone (IJCNN, 2010)

*omeSOM: a software for clustering and visualization of transcriptional and metabolite data mined from interspecific crosses of crop plants. - Diego H. Milone; Georgina Stegmayer; Laura Kamenetzky; Mariana G. Lopez; Je Min Lee; James J. Giovannoni; Fernando Carrari (BMC Bioinform., 2010)

ASAI - Guest Editorial. - Marcelo Alejandro Falappa; Georgina Stegmayer (Inteligencia Artif., 2012)

An evolutionary approach to metabolic pathways search. - Matias Fernando Gerard; Diego H. Milone; Georgina Stegmayer (Inteligencia Artif., 2012)

Data Mining Over Biological Datasets: An Integrated Approach Based on Computational Intelligence. - Georgina Stegmayer; Matias Gerard; Diego H. Milone (IEEE Comput. Intell. Mag., 2012)

Knowledge discovery through ontology matching: An approach based on an Artificial Neural Network model. - Mariano Rubiolo; María Laura Caliusco; Georgina Stegmayer; Mauricio Coronel; M. Gareli Fabrizi (Inf. Sci., 2012)

A Biologically Inspired Validity Measure for Comparison of Clustering Methods over Metabolic Data Sets. - Georgina Stegmayer; Diego H. Milone; Laura Kamenetzky; Mariana G. Lopez; Fernando Carrari (IEEE ACM Trans. Comput. Biol. Bioinform., 2012)

An evolutionary approach for searching metabolic pathways. - Matias Fernando Gerard; Georgina Stegmayer; Diego H. Milone (Comput. Biol. Medicine, 2013)

Clustering biological data with SOMs: On topology preservation in non-linear dimensional reduction. - Diego H. Milone; Georgina Stegmayer; Laura Kamenetzky; Mariana G. Lopez; Fernando Carrari (Expert Syst. Appl., 2013)

Automatic recognition of quarantine citrus diseases. - Georgina Stegmayer; Diego H. Milone; Sergio Garran; Lourdes Burdyn (Expert Syst. Appl., 2013)

Compressing arrays of classifiers using Volterra-neural network: application to face recognition. - Mariano Rubiolo; Georgina Stegmayer; Diego H. Milone (Neural Comput. Appl., 2013)

Stability analysis in overlapped clusters. - David Nazareno Campo; Georgina Stegmayer; Diego H. Milone (Inteligencia Artif., 2014)

A Method to Improve the Analysis of Cluster Ensembles. - Milton Pividori; Georgina Stegmayer; Diego H. Milone (Inteligencia Artif., 2014)

Improving clustering with metabolic pathway data. - Diego H. Milone; Georgina Stegmayer; Mariana G. Lopez; Laura Kamenetzky; Fernando Carrari (BMC Bioinform., 2014)

EvoMS: An evolutionary tool to find de novo metabolic pathways. - Matias Fernando Gerard; Georgina Stegmayer; Diego H. Milone (Biosyst., 2015)

miRNAfe: A comprehensive tool for feature extraction in microRNA prediction. - Cristian A. Yones; Georgina Stegmayer; Laura Kamenetzky; Diego H. Milone (Biosyst., 2015)

Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series. - Mariano Rubiolo; Diego H. Milone; Georgina Stegmayer (IEEE ACM Trans. Comput. Biol. Bioinform., 2015)

A very simple and fast way to access and validate algorithms in reproducible research. - Georgina Stegmayer; Milton Pividori; Diego H. Milone (Briefings Bioinform., 2016)

Evolutionary algorithm for metabolic pathways synthesis. - Matias Fernando Gerard; Georgina Stegmayer; Diego H. Milone (Biosyst., 2016)

Inferring unknown biological function by integration of GO annotations and gene expression data. - Guillermo L. Grinblat; Ariel E. Bayá; Diego H. Milone; Pablo M. Granitto; Georgina Stegmayer (CoRR, 2016)

A new index for clustering validation with overlapped clusters. - David Nazareno Campo; Georgina Stegmayer; Diego H. Milone (Expert Syst. Appl., 2016)

Diversity control for improving the analysis of consensus clustering. - Milton Pividori; Georgina Stegmayer; Diego H. Milone (Inf. Sci., 2016)

Extreme learning machine prediction under high class imbalance in bioinformatics. - Tadeo Rodriguez; Leandro E. Di Persia; Diego H. Milone; Georgina Stegmayer (CLEI, 2017)

High Class-Imbalance in pre-miRNA Prediction: A Novel Approach Based on deepSOM. - Georgina Stegmayer; Cristian A. Yones; Laura Kamenetzky; Diego H. Milone (IEEE ACM Trans. Comput. Biol. Bioinform., 2017)

Extreme learning machines for reverse engineering of gene regulatory networks from expression time series. - Mariano Rubiolo; Diego H. Milone; Georgina Stegmayer (Bioinform., 2018)

Genome-wide pre-miRNA discovery from few labeled examples. - Cristian A. Yones; Georgina Stegmayer; Diego H. Milone (Bioinform., 2018)

Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data. - Guillermo Leale; Ariel E. Bayá; Diego H. Milone; Pablo M. Granitto; Georgina Stegmayer (IEEE ACM Trans. Comput. Biol. Bioinform., 2018)

Predicting novel microRNA: a comprehensive comparison of machine learning approaches. - Georgina Stegmayer; Leandro E. Di Persia; Mariano Rubiolo; Matias Gerard; Milton Pividori; Cristian A. Yones; Leandro A Bugnon; Tadeo Rodriguez; Jonathan Raad; Diego H. Milone (Briefings Bioinform., 2019)

Clustermatch: discovering hidden relations in highly diverse kinds of qualitative and quantitative data without standardization. - Milton Pividori; Andres Cernadas; Luis A. de Haro; Fernando Carrari; Georgina Stegmayer; Diego H. Milone (Bioinform., 2019)

DL4papers: a deep learning approach for the automatic interpretation of scientific articles. - Leandro A Bugnon; Cristian A. Yones; Jonathan Raad; Matias Gerard; Mariano Rubiolo; Gabriela Alejandra Merino; Milton Pividori; Leandro E. Di Persia; Diego H. Milone; Georgina Stegmayer (Bioinform., 2020)

Complexity measures of the mature miRNA for improving pre-miRNAs prediction. - Jonathan Raad; Georgina Stegmayer; Diego H. Milone (Bioinform., 2020)

Deep Neural Architectures for Highly Imbalanced Data in Bioinformatics. - Leandro A Bugnon; Cristian A. Yones; Diego H. Milone; Georgina Stegmayer (IEEE Trans. Neural Networks Learn. Syst., 2020)

Genome-wide discovery of pre-miRNAs: comparison of recent approaches based on machine learning. - Leandro A Bugnon; Cristian A. Yones; Diego H. Milone; Georgina Stegmayer (Briefings Bioinform., 2021)

Novel SARS-CoV-2 encoded small RNAs in the passage to humans. - Gabriela Alejandra Merino; Jonathan Raad; Leandro A Bugnon; Cristian A. Yones; Laura Kamenetzky; Juan Claus; Federico Ariel; Diego H. Milone; Georgina Stegmayer (Bioinform., 2021)

High precision in microRNA prediction: A novel genome-wide approach with convolutional deep residual networks. - Cristian A. Yones; Jonathan Raad; Leandro A Bugnon; Diego H. Milone; Georgina Stegmayer (Comput. Biol. Medicine, 2021)

Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches. - Leandro A Bugnon; Alejandro A. Edera; Santiago Prochetto; Matias Gerard; Jonathan Raad; Emilio Fenoy; Mariano Rubiolo; Uciel Chorostecki; Toni Gabaldón; Federico Ariel; Leandro E. Di Persia; Diego H. Milone; et al. (Briefings Bioinform., 2022)

Anc2vec: embedding gene ontology terms by preserving ancestors relationships. - Alejandro A. Edera; Diego H. Milone; Georgina Stegmayer (Briefings Bioinform., 2022)

Transfer learning in proteins: evaluating novel protein learned representations for bioinformatics tasks. - Emilio Fenoy; Alejandro A. Edera; Georgina Stegmayer (Briefings Bioinform., 2022)

Hierarchical deep learning for predicting GO annotations by integrating protein knowledge. - Gabriela Alejandra Merino; Rabie Saidi; Diego H. Milone; Georgina Stegmayer; Maria Jesus Martin (Bioinform., 2022)

miRe2e: a full end-to-end deep model based on transformers for prediction of pre-miRNAs. - Jonathan Raad; Leandro A Bugnon; Diego H. Milone; Georgina Stegmayer (Bioinform., 2022)

exp2GO: Improving Prediction of Functions in the Gene Ontology With Expression Data. - Leandro E. Di Persia; Tiago Lopez; Agustin Arce; Diego H. Milone; Georgina Stegmayer (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Transfer learning: The key to functionally annotate the protein universe. - Leandro A Bugnon; Emilio Fenoy; Alejandro A. Edera; Jonathan Raad; Georgina Stegmayer; Diego H. Milone (Patterns, 2023)

sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure. - Leandro A Bugnon; Leandro E. Di Persia; Matias Gerard; Jonathan Raad; Santiago Prochetto; Emilio Fenoy; Uciel Chorostecki; Federico Ariel; Georgina Stegmayer; Diego H. Milone (Briefings Bioinform., 2024)

Evaluating large language models for annotating proteins. - Rosario Vitale; Leandro A Bugnon; Emilio Fenoy; Diego H. Milone; Georgina Stegmayer (Briefings Bioinform., 2024)

Comprehensive benchmarking of large language models for RNA secondary structure prediction. - Luciano I Zablocki; Leandro A Bugnon; Matias Gerard; Leandro E. Di Persia; Georgina Stegmayer; Diego H. Milone (Briefings Bioinform., 2024)

gGN: Representing the Gene Ontology as low-rank Gaussian distributions. - Alejandro A. Edera; Georgina Stegmayer; Diego H. Milone (Comput. Biol. Medicine, 2024)

evolSOM: an R Package for evolutionary conservation analysis with SOMs. - Santiago Prochetto; Renata Reinheimer; Georgina Stegmayer (CoRR, 2024)