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ORCIDGeorgina Stegmayer
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2020 – today
- 2024
[j46]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)- [j45]Alejandro A. Edera, Georgina Stegmayer, Diego H. Milone:
gGN: Representing the Gene Ontology as low-rank Gaussian distributions. Comput. Biol. Medicine 183: 109234 (2024) - [i2]Santiago Prochetto, Renata Reinheimer, Georgina Stegmayer:
evolSOM: an R Package for evolutionary conservation analysis with SOMs. CoRR abs/2402.07948 (2024) - 2023
- [j44]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): 100691 (2023) - [j43]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): 999-1008 (2023) - 2022
- [j42]Alejandro A. Edera, Diego H. Milone, Georgina Stegmayer:
Anc2vec: embedding gene ontology terms by preserving ancestors relationships. Briefings Bioinform. 23(2) (2022) - [j41]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:
Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches. Briefings Bioinform. 23(4) (2022) - [j40]Emilio Fenoy, Alejandro A. Edera, Georgina Stegmayer:
Transfer learning in proteins: evaluating novel protein learned representations for bioinformatics tasks. Briefings Bioinform. 23(4) (2022) - [j39]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): 1191-1197 (2022) - [j38]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): 4488-4496 (2022) - 2021
- [j37]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) - [j36]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): 5571-5581 (2021) - [j35]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: 104448 (2021) - 2020
- [j34]Jonathan Raad, Georgina Stegmayer, Diego H. Milone:
Complexity measures of the mature miRNA for improving pre-miRNAs prediction. Bioinform. 36(8): 2319-2327 (2020) - [j33]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): 3499-3506 (2020) - [j32]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): 2857-2867 (2020)
2010 – 2019
- 2019
- [j31]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): 1607-1620 (2019) - [j30]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): 1931-1939 (2019) - 2018
- [j29]Cristian A. Yones, Georgina Stegmayer, Diego H. Milone:
Genome-wide pre-miRNA discovery from few labeled examples. Bioinform. 34(4): 541-549 (2018) - [j28]Mariano Rubiolo, Diego H. Milone, Georgina Stegmayer:
Extreme learning machines for reverse engineering of gene regulatory networks from expression time series. Bioinform. 34(7): 1253-1260 (2018) - [j27]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): 168-180 (2018) - 2017
- [j26]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): 1316-1326 (2017) - [c13]Tadeo Rodriguez, Leandro E. Di Persia, Diego H. Milone, Georgina Stegmayer:
Extreme learning machine prediction under high class imbalance in bioinformatics. CLEI 2017: 1-8 - 2016
- [j25]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): 180-183 (2016) - [j24]Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone:
Evolutionary algorithm for metabolic pathways synthesis. Biosyst. 144: 55-67 (2016) - [j23]David Nazareno Campo, Georgina Stegmayer, Diego H. Milone:
A new index for clustering validation with overlapped clusters. Expert Syst. Appl. 64: 549-556 (2016) - [j22]Milton Pividori, Georgina Stegmayer, Diego H. Milone:
Diversity control for improving the analysis of consensus clustering. Inf. Sci. 361-362: 120-134 (2016) - [i1]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 abs/1608.03672 (2016) - 2015
- [j21]Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone:
EvoMS: An evolutionary tool to find de novo metabolic pathways. Biosyst. 134: 43-47 (2015) - [j20]Cristian A. Yones, Georgina Stegmayer, Laura Kamenetzky, Diego H. Milone:
miRNAfe: A comprehensive tool for feature extraction in microRNA prediction. Biosyst. 138: 1-5 (2015) - [j19]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): 1365-1373 (2015) - 2014
- [j18]Milton Pividori, Georgina Stegmayer, Diego H. Milone:
A Method to Improve the Analysis of Cluster Ensembles. Inteligencia Artif. 17(53): 46-56 (2014) - [j17]David Nazareno Campo, Georgina Stegmayer, Diego H. Milone:
Stability analysis in overlapped clusters. Inteligencia Artif. 17(53): 79-89 (2014) - [j16]Diego H. Milone, Georgina Stegmayer, Mariana G. Lopez, Laura Kamenetzky, Fernando Carrari:
Improving clustering with metabolic pathway data. BMC Bioinform. 15: 101 (2014) - 2013
- [j15]Matias Fernando Gerard, Georgina Stegmayer, Diego H. Milone:
An evolutionary approach for searching metabolic pathways. Comput. Biol. Medicine 43(11): 1704-1712 (2013) - [j14]Georgina Stegmayer, Diego H. Milone, Sergio Garran, Lourdes Burdyn:
Automatic recognition of quarantine citrus diseases. Expert Syst. Appl. 40(9): 3512-3517 (2013) - [j13]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): 3841-3845 (2013) - [j12]Mariano Rubiolo, Georgina Stegmayer, Diego H. Milone:
Compressing arrays of classifiers using Volterra-neural network: application to face recognition. Neural Comput. Appl. 23(6): 1687-1701 (2013) - 2012
- [j11]Matias Fernando Gerard, Diego H. Milone, Georgina Stegmayer:
An evolutionary approach to metabolic pathways search. Inteligencia Artif. 15(49): 1-12 (2012) - [j10]Marcelo Alejandro Falappa, Georgina Stegmayer:
ASAI - Guest Editorial. Inteligencia Artif. 15(50): 1-3 (2012) - [j9]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): 22-34 (2012) - [j8]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: 107-119 (2012) - [j7]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): 706-716 (2012) - 2010
- [j6]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: 438 (2010) - [c12]Mariano Rubiolo, Georgina Stegmayer, Diego H. Milone:
Compressing a neural network classifier using a Volterra-Neural Network model. IJCNN 2010: 1-7
2000 – 2009
- 2009
- [j5]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): 5-13 (2009) - [j4]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): 56-66 (2009) - [j3]Georgina Stegmayer, Omar Chiotti:
Volterra NN-based behavioral model for new wireless communications devices. Neural Comput. Appl. 18(3): 283-291 (2009) - [c11]Diego H. Milone, Georgina Stegmayer, Daniel Beber:
Artificial Life Contest - A Tool for Informal Teaching of Artificial Intelligence. CSEDU (1) 2009: 119-124 - [c10]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: 2983-2989 - [c9]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: 66-73 - 2008
- [c8]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: 255-264 - 2007
- [c7]Georgina Stegmayer:
Neural Networks and Volterra series for modeling new wireless communication devices. IJCNN 2007: 489-494 - [c6]Georgina Stegmayer, María Laura Caliusco, Omar Chiotti, María Rosa Galli:
ANN-Agent for Distributed Knowledge Source Discovery. OTM Workshops (1) 2007: 467-476 - 2006
- [c5]Georgina Stegmayer, Omar Chiotti:
Neural Networks applied to wireless communications. IFIP AI 2006: 129-138 - 2005
- [j2]Georgina Stegmayer, Omar Chiotti:
Novel Neural Network application to nonlinear electronic devices: building a Volterra series model. Inteligencia Artif. 9(26): 19-27 (2005) - [c4]Georgina Stegmayer, Omar Chiotti, Giancarlo Orengo:
A Neural Network that helps building a Nonlinear Dynamical model of a Power Amplifier. ESANN 2005: 539-544 - [c3]Georgina Stegmayer:
Comparison of Volterra Models Extracted from a Neural Network for Nonlinear Systems Modeling. ICANN (2) 2005: 457-463 - [c2]Georgina Stegmayer, Omar Chiotti:
Identification of Frequency-Domain Volterra Model Using Neural Networks. ICANN (2) 2005: 465-471 - 2002
- [j1]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) - 2001
- [c1]Georgina Stegmayer, María Laura Caliusco, Omar Chiotti, María Rosa Galli:
Knowledge Component of a Multiagent Distributed Decision Support System. JIISIC 2001: 79-90
Coauthor Index
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