Georgina Stegmayer

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 27

Top Topics

Extreme Learning Machines

Metabolic Pathways

Scientific Articles

Top Venues

Briefings Bioinform.

IEEE ACM Trans. Comput. Biol. Bioinform.

Publications

Leandro A Bugnon, Leandro E. Di Persia, Matias Gerard, Jonathan Raad, Santiago Prochetto, Emilio Fenoy, Uciel Chorostecki, Federico Ariel, Georgina Stegmayer, Diego H. Milone
sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure. Briefings Bioinform. 25 (4) (2024)
Santiago Prochetto, Renata Reinheimer, Georgina Stegmayer
evolSOM: an R Package for evolutionary conservation analysis with SOMs. CoRR (2024)
Leandro E. Di Persia, Tiago Lopez, Agustin Arce, Diego H. Milone, Georgina Stegmayer
exp2GO: Improving Prediction of Functions in the Gene Ontology With Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 20 (2) (2023)
Leandro A Bugnon, Emilio Fenoy, Alejandro A. Edera, Jonathan Raad, Georgina Stegmayer, Diego H. Milone
Transfer learning: The key to functionally annotate the protein universe. Patterns 4 (2) (2023)
Alejandro A. Edera, Diego H. Milone, Georgina Stegmayer
Anc2vec: embedding gene ontology terms by preserving ancestors relationships. Briefings Bioinform. 23 (2) (2022)
Emilio Fenoy, Alejandro A. Edera, Georgina Stegmayer
Transfer learning in proteins: evaluating novel protein learned representations for bioinformatics tasks. Briefings Bioinform. 23 (4) (2022)
Gabriela Alejandra Merino, Rabie Saidi, Diego H. Milone, Georgina Stegmayer, Maria Jesus Martin
Hierarchical deep learning for predicting GO annotations by integrating protein knowledge. Bioinform. 38 (19) (2022)
Jonathan Raad, Leandro A Bugnon, Diego H. Milone, Georgina Stegmayer
miRe2e: a full end-to-end deep model based on transformers for prediction of pre-miRNAs. Bioinform. 38 (5) (2022)
Leandro A Bugnon, Alejandro A. Edera, S. Prochetto, Matias Gerard, Jonathan Raad, E. Fenoy, Mariano Rubiolo, Uciel Chorostecki, Toni Gabaldón, Federico Ariel, Leandro E. Di Persia, Diego H. Milone, Georgina Stegmayer
Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches. Briefings Bioinform. 23 (4) (2022)
Leandro A Bugnon, Cristian A. Yones, Diego H. Milone, Georgina Stegmayer
Genome-wide discovery of pre-miRNAs: comparison of recent approaches based on machine learning. Briefings Bioinform. 22 (3) (2021)
Gabriela Alejandra Merino, Jonathan Raad, Leandro A Bugnon, Cristian A. Yones, Laura Kamenetzky, Juan Claus, Federico Ariel, Diego H. Milone, Georgina Stegmayer
Novel SARS-CoV-2 encoded small RNAs in the passage to humans. Bioinform. 36 (24) (2021)
Cristian A. Yones, Jonathan Raad, Leandro A Bugnon, Diego H. Milone, Georgina Stegmayer
High precision in microRNA prediction: A novel genome-wide approach with convolutional deep residual networks. Comput. Biol. Medicine 134 (2021)
Jonathan Raad, Georgina Stegmayer, Diego H. Milone
Complexity measures of the mature miRNA for improving pre-miRNAs prediction. Bioinform. 36 (8) (2020)
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
DL4papers: a deep learning approach for the automatic interpretation of scientific articles. Bioinform. 36 (11) (2020)
Leandro A Bugnon, Cristian A. Yones, Diego H. Milone, Georgina Stegmayer
Deep Neural Architectures for Highly Imbalanced Data in Bioinformatics. IEEE Trans. Neural Networks Learn. Syst. 31 (8) (2020)
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
Predicting novel microRNA: a comprehensive comparison of machine learning approaches. Briefings Bioinform. 20 (5) (2019)
Milton Pividori, Andres Cernadas, Luis A. de Haro, Fernando Carrari, Georgina Stegmayer, Diego H. Milone
Clustermatch: discovering hidden relations in highly diverse kinds of qualitative and quantitative data without standardization. Bioinform. 35 (11) (2019)
Guillermo Leale, Ariel E. Bayá, Diego H. Milone, Pablo M. Granitto, Georgina Stegmayer
Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 15 (1) (2018)
Cristian A. Yones, Georgina Stegmayer, Diego H. Milone
Genome-wide pre-miRNA discovery from few labeled examples. Bioinform. 34 (4) (2018)
Mariano Rubiolo, Diego H. Milone, Georgina Stegmayer
Extreme learning machines for reverse engineering of gene regulatory networks from expression time series. Bioinform. 34 (7) (2018)
Georgina Stegmayer, Cristian A. Yones, Laura Kamenetzky, Diego H. Milone
High Class-Imbalance in pre-miRNA Prediction: A Novel Approach Based on deepSOM. IEEE ACM Trans. Comput. Biol. Bioinform. 14 (6) (2017)
Tadeo Rodriguez, Leandro E. Di Persia, Diego H. Milone, Georgina Stegmayer
Extreme learning machine prediction under high class imbalance in bioinformatics. CLEI (2017)
Georgina Stegmayer, Milton Pividori, Diego H. Milone
A very simple and fast way to access and validate algorithms in reproducible research. Briefings Bioinform. 17 (1) (2016)
Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone
Evolutionary algorithm for metabolic pathways synthesis. Biosyst. 144 (2016)
Guillermo L. Grinblat, Ariel E. Bayá, Diego H. Milone, Pablo M. Granitto, Georgina Stegmayer
Inferring unknown biological function by integration of GO annotations and gene expression data. CoRR (2016)
David Nazareno Campo, Georgina Stegmayer, Diego H. Milone
A new index for clustering validation with overlapped clusters. Expert Syst. Appl. 64 (2016)
Milton Pividori, Georgina Stegmayer, Diego H. Milone
Diversity control for improving the analysis of consensus clustering. Inf. Sci. (2016)
Mariano Rubiolo, Diego H. Milone, Georgina Stegmayer
Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series. IEEE ACM Trans. Comput. Biol. Bioinform. 12 (6) (2015)
Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone
EvoMS: An evolutionary tool to find de novo metabolic pathways. Biosyst. 134 (2015)
Cristian A. Yones, Georgina Stegmayer, Laura Kamenetzky, Diego H. Milone
miRNAfe: A comprehensive tool for feature extraction in microRNA prediction. Biosyst. 138 (2015)
Milton Pividori, Georgina Stegmayer, Diego H. Milone
A Method to Improve the Analysis of Cluster Ensembles. Inteligencia Artif. 17 (53) (2014)
David Nazareno Campo, Georgina Stegmayer, Diego H. Milone
Stability analysis in overlapped clusters. Inteligencia Artif. 17 (53) (2014)
Diego H. Milone, Georgina Stegmayer, Mariana G. Lopez, Laura Kamenetzky, Fernando Carrari
Improving clustering with metabolic pathway data. BMC Bioinform. 15 (2014)
Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone
An evolutionary approach for searching metabolic pathways. Comput. Biol. Medicine 43 (11) (2013)
Diego H. Milone, Georgina Stegmayer, Laura Kamenetzky, Mariana G. Lopez, Fernando Carrari
Clustering biological data with SOMs: On topology preservation in non-linear dimensional reduction. Expert Syst. Appl. 40 (9) (2013)
Georgina Stegmayer, Diego H. Milone, Sergio Garran, Lourdes Burdyn
Automatic recognition of quarantine citrus diseases. Expert Syst. Appl. 40 (9) (2013)
Mariano Rubiolo, Georgina Stegmayer, Diego H. Milone
Compressing arrays of classifiers using Volterra-neural network: application to face recognition. Neural Comput. Appl. 23 (6) (2013)
Georgina Stegmayer, Matias Gerard, Diego H. Milone
Data Mining Over Biological Datasets: An Integrated Approach Based on Computational Intelligence. IEEE Comput. Intell. Mag. 7 (4) (2012)
Matias Fernando Gerard, Diego H. Milone, Georgina Stegmayer
An evolutionary approach to metabolic pathways search. Inteligencia Artif. 15 (49) (2012)
Marcelo Alejandro Falappa, Georgina Stegmayer
ASAI - Guest Editorial. Inteligencia Artif. 15 (50) (2012)
Mariano Rubiolo, María Laura Caliusco, Georgina Stegmayer, Mauricio Coronel, M. Gareli Fabrizi
Knowledge discovery through ontology matching: An approach based on an Artificial Neural Network model. Inf. Sci. 194 (2012)
Georgina Stegmayer, Diego H. Milone, Laura Kamenetzky, Mariana G. Lopez, Fernando Carrari
A Biologically Inspired Validity Measure for Comparison of Clustering Methods over Metabolic Data Sets. IEEE ACM Trans. Comput. Biol. Bioinform. 9 (3) (2012)
Mariano Rubiolo, Georgina Stegmayer, Diego H. Milone
Compressing a neural network classifier using a Volterra-Neural Network model. IJCNN (2010)
Diego H. Milone, Georgina Stegmayer, Laura Kamenetzky, Mariana G. Lopez, Je Min Lee, James J. Giovannoni, Fernando Carrari
*omeSOM: a software for clustering and visualization of transcriptional and metabolite data mined from interspecific crosses of crop plants. BMC Bioinform. 11 (2010)
Mariano Rubiolo, María Laura Caliusco, Georgina Stegmayer, Matías Gareli, Mauricio Coronel
Knowledge Source Discovery: An Experience Using Ontologies, WordNet and Artificial Neural Networks. KES (2) (2009)
Diego H. Milone, Georgina Stegmayer, Matias Gerard, Laura Kamenetzky, Mariana G. Lopez, Fernando Carrari
Métodos de agrupamiento no supervisado para la integración de datos genómicos y metabólicos de múltiples líneas de introgresión. Inteligencia Artif. 13 (44) (2009)
Georgina Stegmayer, Diego H. Milone, Laura Kamenetzky, Mariana G. Lopez, Fernando Carrari
Neural network model for integration and visualization of introgressed genome and metabolite data. IJCNN (2009)
Georgina Stegmayer, Omar Chiotti
Volterra NN-based behavioral model for new wireless communications devices. Neural Comput. Appl. 18 (3) (2009)
D. Capello, César Ernesto Martínez, Diego H. Milone, Georgina Stegmayer
Array of Multilayer Perceptrons with No-class Resampling Training for Face Recognition. Inteligencia Artif. 13 (44) (2009)
Diego H. Milone, Georgina Stegmayer, Daniel Beber
Artificial Life Contest - A Tool for Informal Teaching of Artificial Intelligence. CSEDU (1) (2009)
Georgina Stegmayer, Jorge R. Vega, Luis M. Gugliotta, Omar Chiotti
Estimation of the Particle Size Distribution of a Latex using a General Regression Neural Network. IFIP AI (2008)
Georgina Stegmayer
Neural Networks and Volterra series for modeling new wireless communication devices. IJCNN (2007)
Georgina Stegmayer, María Laura Caliusco, Omar Chiotti, María Rosa Galli
ANN-Agent for Distributed Knowledge Source Discovery. OTM Workshops (1) (2007)
Georgina Stegmayer, Omar Chiotti
Neural Networks applied to wireless communications. IFIP AI (2006)
Georgina Stegmayer, Omar Chiotti, Giancarlo Orengo
A Neural Network that helps building a Nonlinear Dynamical model of a Power Amplifier. ESANN (2005)
Georgina Stegmayer
Comparison of Volterra Models Extracted from a Neural Network for Nonlinear Systems Modeling. ICANN (2) (2005)
Georgina Stegmayer, Omar Chiotti
Novel Neural Network application to nonlinear electronic devices: building a Volterra series model. Inteligencia Artif. 9 (26) (2005)
Georgina Stegmayer, Omar Chiotti
Identification of Frequency-Domain Volterra Model Using Neural Networks. ICANN (2) (2005)
Georgina Stegmayer, María Laura Caliusco, Omar Chiotti, María Rosa Galli
Knowledge Component of a Multiagent Distributed Decision Support System. CLEI Electron. J. 5 (1) (2002)
Georgina Stegmayer, María Laura Caliusco, Omar Chiotti, María Rosa Galli
Knowledge Component of a Multiagent Distributed Decision Support System. JIISIC (2001)