Georgina Stegmayer

According to our database, Georgina Stegmayer authored at least 58 papers between 2002 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

evolSOM: an R Package for evolutionary conservation analysis with SOMs.

Santiago Prochetto, Renata Reinheimer, Georgina Stegmayer

CoRR, 2024

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, February, 2023

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

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

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

Transfer learning in proteins: evaluating novel protein learned representations for bioinformatics tasks.

Emilio Fenoy, Alejandro A. Edera, Georgina Stegmayer

Briefings Bioinform., 2022

Anc2vec: embedding gene ontology terms by preserving ancestors relationships.

Alejandro A. Edera, Diego H. Milone, Georgina Stegmayer

Briefings Bioinform., 2022

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, Georgina Stegmayer

Briefings Bioinform., 2022

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

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

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

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

Complexity measures of the mature miRNA for improving pre-miRNAs prediction.

Jonathan Raad, Georgina Stegmayer, Diego H. Milone

Bioinform., 2020

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

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

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

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

Genome-wide pre-miRNA discovery from few labeled examples.

Cristian A. Yones, Georgina Stegmayer, Diego H. Milone

Bioinform., 2018

Extreme learning machines for reverse engineering of gene regulatory networks from expression time series.

Mariano Rubiolo, Diego H. Milone, Georgina Stegmayer

Bioinform., 2018

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 machine prediction under high class imbalance in bioinformatics.

Tadeo Rodriguez, Leandro E. Di Persia, Diego H. Milone, Georgina Stegmayer

Proceedings of the 2017 XLIII Latin American Computer Conference, 2017

2016

Diversity control for improving the analysis of consensus clustering.

Milton Pividori, Georgina Stegmayer, Diego H. Milone

Inf. Sci., 2016

A new index for clustering validation with overlapped clusters.

David Nazareno Campo, Georgina Stegmayer, Diego H. Milone

Expert Syst. Appl., 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

Evolutionary algorithm for metabolic pathways synthesis.

Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone

Biosyst., 2016

A very simple and fast way to access and validate algorithms in reproducible research.

Georgina Stegmayer, Milton Pividori, Diego H. Milone

Briefings Bioinform., 2016

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

miRNAfe: A comprehensive tool for feature extraction in microRNA prediction.

Cristian A. Yones, Georgina Stegmayer, Laura Kamenetzky, Diego H. Milone

Biosyst., 2015

EvoMS: An evolutionary tool to find de novo metabolic pathways.

Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone

Biosyst., 2015

2014

Improving clustering with metabolic pathway data.

Diego H. Milone, Georgina Stegmayer, Mariana G. Lopez, Laura Kamenetzky, Fernando Carrari

BMC Bioinform., 2014

A Method to Improve the Analysis of Cluster Ensembles.

Milton Pividori, Georgina Stegmayer, Diego H. Milone

Inteligencia Artif., 2014

Stability analysis in overlapped clusters.

David Nazareno Campo, Georgina Stegmayer, Diego H. Milone

Inteligencia Artif., 2014

2013

Compressing arrays of classifiers using Volterra-neural network: application to face recognition.

Mariano Rubiolo, Georgina Stegmayer, Diego H. Milone

Neural Comput. Appl., 2013

Automatic recognition of quarantine citrus diseases.

Georgina Stegmayer, Diego H. Milone, Sergio Garran, Lourdes Burdyn

Expert Syst. Appl., 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

An evolutionary approach for searching metabolic pathways.

Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone

Comput. Biol. Medicine, 2013

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

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

Data Mining Over Biological Datasets: An Integrated Approach Based on Computational Intelligence.

Georgina Stegmayer, Matias Gerard, Diego H. Milone

IEEE Comput. Intell. Mag., 2012

An evolutionary approach to metabolic pathways search.

Matias Fernando Gerard, Diego H. Milone, Georgina Stegmayer

Inteligencia Artif., 2012

ASAI - Guest Editorial.

Marcelo Alejandro Falappa, Georgina Stegmayer

Inteligencia Artif., 2012

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

Compressing a neural network classifier using a Volterra-Neural Network model.

Mariano Rubiolo, Georgina Stegmayer, Diego H. Milone

Proceedings of the International Joint Conference on Neural Networks, 2010

2009

Volterra NN-based behavioral model for new wireless communications devices.

Georgina Stegmayer, Omar Chiotti

Neural Comput. Appl., 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

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

Knowledge Source Discovery: An Experience Using Ontologies, WordNet and Artificial Neural Networks.

Mariano Rubiolo, María Laura Caliusco, Georgina Stegmayer, Matías Gareli, Mauricio Coronel

Proceedings of the Knowledge-Based and Intelligent Information and Engineering Systems, 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

Proceedings of the International Joint Conference on Neural Networks, 2009

Artificial Life Contest - A Tool for Informal Teaching of Artificial Intelligence.

Diego H. Milone, Georgina Stegmayer, Daniel Beber

Proceedings of the CSEDU 2009 - Proceedings of the First International Conference on Computer Supported Education, Lisboa, Portugal, March 23-26, 2009, 2009

2008

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

Proceedings of the Artificial Intelligence in Theory and Practice II, 2008

2007

ANN-Agent for Distributed Knowledge Source Discovery.

Georgina Stegmayer, María Laura Caliusco, Omar Chiotti, María Rosa Galli

Proceedings of the On the Move to Meaningful Internet Systems 2007: OTM 2007 Workshops, 2007

Neural Networks and Volterra series for modeling new wireless communication devices.

Georgina Stegmayer

Proceedings of the International Joint Conference on Neural Networks, 2007

2006

Neural Networks applied to wireless communications.

Georgina Stegmayer, Omar Chiotti

Proceedings of the Artificial Intelligence in Theory and Practice, 2006

2005

Novel Neural Network application to nonlinear electronic devices: building a Volterra series model.

Georgina Stegmayer, Omar Chiotti

Inteligencia Artif., 2005

Identification of Frequency-Domain Volterra Model Using Neural Networks.

Georgina Stegmayer, Omar Chiotti

Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

Comparison of Volterra Models Extracted from a Neural Network for Nonlinear Systems Modeling.

Georgina Stegmayer

Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

A Neural Network that helps building a Nonlinear Dynamical model of a Power Amplifier.

Georgina Stegmayer, Omar Chiotti, Giancarlo Orengo

Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005

2002

Knowledge Component of a Multiagent Distributed Decision Support System.

Georgina Stegmayer, María Laura Caliusco, Omar Chiotti, María Rosa Galli

CLEI Electron. J., 2002