| Cumida: An extensively curated microarray database for benchmarking and testing of machine learning approaches in cancer research BC Feltes, EB Chandelier, BI Grisci, M Dorn Journal of Computational Biology 26 (4), 376-386, 2019 | 92 | 2019 |
| Aromatic rings commonly used in medicinal chemistry: force fields comparison and interactions with water toward the design of new chemical entities MD Polêto, VH Rusu, BI Grisci, M Dorn, RD Lins, H Verli Frontiers in pharmacology 9, 395, 2018 | 56 | 2018 |
| APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction B Borguesan, MB e Silva, B Grisci, M Inostroza-Ponta, M Dorn Computational biology and chemistry 59, 142-157, 2015 | 52 | 2015 |
| Neuroevolution as a tool for microarray gene expression pattern identification in cancer research BI Grisci, BC Feltes, M Dorn Journal of biomedical informatics 89, 122-133, 2019 | 35 | 2019 |
| Relevance aggregation for neural networks interpretability and knowledge discovery on tabular data BI Grisci, MJ Krause, M Dorn Information sciences 559, 111-129, 2021 | 25 | 2021 |
| Neuroevolution of neural network architectures using CoDeepNEAT and Keras JS Bohrer, BI Grisci, M Dorn arXiv preprint arXiv:2002.04634, 2020 | 15 | 2020 |
| Comparison of machine learning techniques to handle imbalanced COVID-19 CBC datasets M Dorn, BI Grisci, PH Narloch, BC Feltes, E Avila, A Kahmann, CS Alho PeerJ Computer Science 7, e670, 2021 | 14 | 2021 |
| Perspectives and applications of machine learning for evolutionary developmental biology BC Feltes, BI Grisci, J de Faria Poloni, M Dorn Molecular omics 14 (5), 289-306, 2018 | 10 | 2018 |
| Development of GROMOS-compatible parameter set for simulations of chalcones and flavonoids PR Arantes, MD Polêto, EBO John, C Pedebos, BI Grisci, M Dorn, ... The Journal of Physical Chemistry B 123 (5), 994-1008, 2019 | 9 | 2019 |
| NEAT-FLEX: Predicting the conformational flexibility of amino acids using neuroevolution of augmenting topologies B Grisci, M Dorn Journal of Bioinformatics and Computational Biology 15 (03), 1750009, 2017 | 8 | 2017 |
| Microarray classification and gene selection with FS-NEAT BI Grisci, BC Feltes, M Dorn 2018 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2018 | 6 | 2018 |
| ConfID: an analytical method for conformational characterization of small molecules using molecular dynamics trajectories MD Polêto, BI Grisci, M Dorn, H Verli Bioinformatics 36 (11), 3576-3577, 2020 | 5 | 2020 |
| Predicting protein structural features with neuroevolution of augmenting topologies B Grisci, M Dorn 2016 International Joint Conference on Neural Networks (IJCNN), 873-880, 2016 | 3 | 2016 |
| Perspectives on risk prioritization of data center vulnerabilities using rank aggregation and multi-objective optimization B Grisci, G Kuhn, F Colombelli, V Matter, L Lima, K Heinen, M Pegoraro, ... arXiv preprint arXiv:2202.07466, 2022 | 2 | 2022 |
| The use of gene expression datasets in feature selection research: 20 years of inherent bias? BI Grisci, BC Feltes, J de Faria Poloni, PH Narloch, M Dorn Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 14 (2 …, 2023 | 1 | 2023 |
| Analysis and comparison of feature selection methods towards performance and stability MC Barbieri, BI Grisci, M Dorn Expert Systems with Applications 249 (Part B), 123667, 2024 | | 2024 |
| Multi-objective prioritization for data center vulnerability remediation F Colombelli, VK Matter, BI Grisci, L Lima, K Heinen, M Borges, SJ Rigo, ... 2022 IEEE Congress on Evolutionary Computation (CEC), 01-08, 2022 | | 2022 |
| N3O: a NEAT expansion for improving classification and feature selection applied to microarray data BI Grisci MSc Dissertation, Federal University of Rio Grande do Sul, 2018 | | 2018 |
| Predição da flexibilidade de aminoácidos utilizando NeuroEvolução de Topologias Crescentes BI Grisci BSc Final Project, Federal University of Rio Grande do Sul, 2016 | | 2016 |
Márcio DornFederal University of Rio Grande do SulVerified email at inf.ufrgs.br
