| Automatic recognition of quarantine citrus diseases G Stegmayer, DH Milone, S Garran, L Burdyn Expert systems with applications 40 (9), 3512-3517, 2013 | 77 | 2013 |
| A neural network model for estimating the particle size distribution of dilute latex from multiangle dynamic light scattering measurements LM Gugliotta, GS Stegmayer, LA Clementi, VDG Gonzalez, RJ Minari, ... Particle & Particle Systems Characterization 26 (1‐2), 41-52, 2009 | 70 | 2009 |
| Knowledge discovery through ontology matching: An approach based on an Artificial Neural Network model M Rubiolo, ML Caliusco, G Stegmayer, M Coronel, MG Fabrizi Information Sciences 194, 107-119, 2012 | 49 | 2012 |
| Predicting novel microRNA: a comprehensive comparison of machine learning approaches G Stegmayer, LE Di Persia, M Rubiolo, M Gerard, M Pividori, C Yones, ... Briefings in bioinformatics 20 (5), 1607-1620, 2019 | 47 | 2019 |
| * omeSOM: a software for clustering and visualization of transcriptional and metabolite data mined from interspecific crosses of crop plants DH Milone, GS Stegmayer, L Kamenetzky, M López, JM Lee, ... BMC bioinformatics 11, 1-10, 2010 | 43 | 2010 |
| Deep neural architectures for highly imbalanced data in bioinformatics LA Bugnon, C Yones, DH Milone, G Stegmayer IEEE Transactions on Neural Networks and Learning Systems 31 (8), 2857-2867, 2019 | 41 | 2019 |
| High class-imbalance in pre-miRNA prediction: a novel approach based on deepSOM G Stegmayer, C Yones, L Kamenetzky, DH Milone IEEE/ACM transactions on computational biology and bioinformatics 14 (6 …, 2016 | 37 | 2016 |
| Towards a Volterra series representation from a Neural Network model G Stegmayer, M Pirola, G Orengo, O Chiotti WSEAS Transactions on Systems 3 (2), 432-437, 2004 | 37 | 2004 |
| miRNAfe: a comprehensive tool for feature extraction in microRNA prediction CA Yones, G Stegmayer, L Kamenetzky, DH Milone Biosystems 138, 1-5, 2015 | 33 | 2015 |
| Extreme learning machines for reverse engineering of gene regulatory networks from expression time series M Rubiolo, DH Milone, G Stegmayer Bioinformatics 34 (7), 1253-1260, 2018 | 32 | 2018 |
| Metabolic analyses of interspecific tomato recombinant inbred lines for fruit quality improvement MG López, MI Zanor, GR Pratta, G Stegmayer, SB Boggio, M Conte, ... Metabolomics 11, 1416-1431, 2015 | 31 | 2015 |
| A new index for clustering validation with overlapped clusters DN Campo, G Stegmayer, DH Milone Expert Systems with Applications 64, 549-556, 2016 | 30 | 2016 |
| Volterra series and neural networks to model an electronic device nonlinear behavior G Stegmayer 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No …, 2004 | 30 | 2004 |
| Novel SARS-CoV-2 encoded small RNAs in the passage to humans GA Merino, J Raad, LA Bugnon, C Yones, L Kamenetzky, J Claus, F Ariel, ... Bioinformatics 36 (24), 5571-5581, 2020 | 27 | 2020 |
| Data mining over biological datasets: An integrated approach based on computational intelligence G Stegmayer, M Gerard, DH Milone IEEE Computational Intelligence Magazine 7 (4), 22-34, 2012 | 26 | 2012 |
| Alternative use of miRNA-biogenesis co-factors in plants at low temperatures DA Ré, PLM Lang, C Yones, AL Arce, G Stegmayer, D Milone, ... Development 146 (5), dev172932, 2019 | 25 | 2019 |
| Semantic web technologies and artificial neural networks for intelligent web knowledge source discovery ML Caliusco, G Stegmayer Emergent web intelligence: Advanced semantic technologies, 17-36, 2010 | 25 | 2010 |
| Diversity control for improving the analysis of consensus clustering M Pividori, G Stegmayer, DH Milone Information Sciences 361, 120-134, 2016 | 21 | 2016 |
| A biologically inspired validity measure for comparison of clustering methods over metabolic data sets G Stegmayer, DH Milone, L Kamenetzky, MG López, F Carrari IEEE/ACM Transactions on Computational Biology and Bioinformatics 9 (3), 706-716, 2012 | 21 | 2012 |
| Neural network model for integration and visualization of introgressed genome and metabolite data G Stegmayer, D Milone, L Kamenetzky, M Lopez, F Carrari 2009 International Joint Conference on Neural Networks, 2983-2989, 2009 | 21 | 2009 |
Diego H. MiloneFull Professor UNL. Principal Investigator CONICET.Verified email at sinc.unl.edu.ar
