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Márcio Dorn
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2020 – today
- 2024
- [j35]Matheus Cezimbra Barbieri
, Bruno Iochins Grisci
Analysis and comparison of feature selection methods towards performance and stability. Expert Syst. Appl. 249: 123667 (2024) - [j34]Jonas da Silveira Bohrer
Enhancing classification with hybrid feature selection: A multi-objective genetic algorithm for high-dimensional data. Expert Syst. Appl. 255: 124518 (2024) - [j33]Bruno Iochins Grisci
The use of gene expression datasets in feature selection research: 20 years of inherent bias? WIREs Data. Mining. Knowl. Discov. 14(2) (2024) - [c39]Jorge Cubillos-Chaparro, Márcio Dorn, Manuel Villalobos-Cid, Mario Inostroza-Ponta:
A Multiobjective Evolutionary Algorithm for Colon Cancer Biomarkers Identification on Gene Expression Data. CIBCB 2024: 1-8 - 2023
- [j32]Manuel Villalobos-Cid
An evolutionary algorithm based on parsimony for the multiobjective phylogenetic network inference problem. Appl. Soft Comput. 139: 110270 (2023) - [j31]Adrian Kummerländer
Implicit propagation of directly addressed grids in lattice Boltzmann methods. Concurr. Comput. Pract. Exp. 35(8) (2023) - [j30]Bruno César Feltes
NIAS-Server 2.0: A versatile complementary tool for structural biology studies. J. Comput. Chem. 44(18): 1610-1623 (2023) - [c38]Gabriel Dominico, Juliana S. Bernardes, Leonardo Da Luz Dorneles
Multi-Objective Wrapper Differential Evolution with Guided Initial Population for Feature Selection. CEC 2023: 1-8 - [c37]Leonardo Da Luz Dorneles
Benchmark Problems on GPU: Accelerating Experiments on Metaheuristics. CEC 2023: 1-8 - [c36]Mateus Boiani
A Fitness-Based Migration Policy for Biased Random-Key Genetic Algorithms. EvoApplications@EvoStar 2023: 396-410 - 2022
- [j29]Itamar José Guimarães Nunes
Gene Expression Variation Analysis (GEVA): A new R package to evaluate variations in differential expression in multiple biological conditions. J. Biomed. Informatics 129: 104053 (2022) - [c35]Mateus Boiani
A Multi-population Schema Designed for Biased Random-Key Genetic Algorithms on Continuous Optimisation Problems. BRACIS (1) 2022: 444-457 - 2021
- [j28]Robin Trunk, Colin Bretl, Gudrun Thäter, Hermann Nirschl, Márcio Dorn
A Study on Shape-Dependent Settling of Single Particles with Equal Volume Using Surface Resolved Simulations. Comput. 9(4): 40 (2021) - [j27]Bruno Iochins Grisci
Relevance aggregation for neural networks interpretability and knowledge discovery on tabular data. Inf. Sci. 559: 111-129 (2021) - [j26]Bruno César Feltes
Benchmarking and Testing Machine Learning Approaches with BARRA: CuRDa, a Curated RNA-Seq Database for Cancer Research. J. Comput. Biol. 28(9): 931-944 (2021) - [j25]Éderson Sales Moreira Pinto
Modifying the catalytic preference of alpha-amylase toward n-alkanes for bioremediation purposes using in silico strategies. J. Comput. Chem. 42(22): 1540-1551 (2021) - [j24]Márcio Dorn
Comparison of machine learning techniques to handle imbalanced COVID-19 CBC datasets. PeerJ Comput. Sci. 7: e670 (2021) - [c34]Mariel Barbachan e Silva, Pedro Henrique Narloch, Márcio Dorn, Pilib Ó Broin:
Optimisation of Cancer Status Prediction Pipelines using Bio-Inspired Computing. CEC 2021: 442-449 - [c33]Pedro Henrique Narloch
Evaluating the Success-History Based Adaptive Differential Evolution in the Protein Structure Prediction Problem. EvoApplications 2021: 194-209 - [c32]Sebastián Aliaga-Rojas, Manuel Villalobos-Cid
A multi-objective approach for the protein structure prediction problem. SCCC 2021: 1-8 - 2020
- [j23]Marcelo Depólo Polêto, Bruno Iochins Grisci
ConfID: an analytical method for conformational characterization of small molecules using molecular dynamics trajectories. Bioinform. 36(11): 3576-3577 (2020) - [j22]Fabian Klemens, Benjamin Förster, Márcio Dorn
Solving fluid flow domain identification problems with adjoint lattice Boltzmann methods. Comput. Math. Appl. 79(1): 17-33 (2020) - [j21]Mario Inostroza-Ponta
Exploring the high selectivity of 3-D protein structures using distributed memetic algorithms. J. Comput. Sci. 41: 101087 (2020) - [j20]Leonardo de Lima Corrêa, Márcio Dorn
A multi-population memetic algorithm for the 3-D protein structure prediction problem. Swarm Evol. Comput. 55: 100677 (2020) - [c31]Leonardo de Lima Correa, Luciana Arantes, Pierre Sens, Mario Inostroza-Ponta, Márcio Dorn
A dynamic evolutionary multi-agent system to predict the 3D structure of proteins. CEC 2020: 1-8 - [c30]Pedro Henrique Narloch, Mathias J. Krause, Márcio Dorn
Multi-Objective Differential Evolution Algorithms for the Protein Structure Prediction Problem. CEC 2020: 1-8 - [c29]Alfeu Uzai Tavares, Márcio Dorn
Determining the Conformational Flexibility of Disaccharides with an Adaptive Differential Evolution Approach. CEC 2020: 1-8 - [c28]Pedro Henrique Narloch
Differential Evolution Multi-Objective for Tertiary Protein Structure Prediction. EvoApplications 2020: 165-180 - [i2]Jonas da Silveira Bohrer, Bruno Iochins Grisci
Neuroevolution of Neural Network Architectures Using CoDeepNEAT and Keras. CoRR abs/2002.04634 (2020) - [i1]Eduardo Avila, Márcio Dorn, Clarice Sampaio Alho, Alessandro Kahmann:
Hemogram Data as a Tool for Decision-making in COVID-19 Management: Applications to Resource Scarcity Scenarios. CoRR abs/2005.10227 (2020)
2010 – 2019
- 2019
- [j19]Bruno Iochins Grisci
Neuroevolution as a tool for microarray gene expression pattern identification in cancer research. J. Biomed. Informatics 89: 122-133 (2019) - [j18]Bruno César Feltes
CuMiDa: An Extensively Curated Microarray Database for Benchmarking and Testing of Machine Learning Approaches in Cancer Research. J. Comput. Biol. 26(4): 376-386 (2019) - [j17]Pablo Felipe Leonhart, Eduardo Spieler, Rodrigo Ligabue-Braun
A biased random key genetic algorithm for the protein-ligand docking problem. Soft Comput. 23(12): 4155-4176 (2019) - [j16]Manuel Villalobos-Cid
A Memetic Algorithm Based on an NSGA-II Scheme for Phylogenetic Tree Inference. IEEE Trans. Evol. Comput. 23(5): 776-787 (2019) - [c27]Pedro Henrique Narloch, Márcio Dorn
Rosetta Ligand-Protein Docking with Self-Adaptive Differential Evolution. BIBE 2019: 23-30 - [c26]Pedro Henrique Narloch
A Knowledge Based Differential Evolution Algorithm for Protein Structure Prediction. EvoApplications 2019: 343-359 - [c25]Pablo Felipe Leonhart
A Biased Random Key Genetic Algorithm with Local Search Chains for Molecular Docking. EvoApplications 2019: 360-376 - [c24]Pedro Henrique Narloch
A Knowledge Based Self-Adaptive Differential Evolution Algorithm for Protein Structure Prediction. ICCS (3) 2019: 87-100 - [c23]Leonardo de Lima Corrêa, Márcio Dorn
A Multi-objective Swarm-Based Algorithm for the Prediction of Protein Structures. ICCS (3) 2019: 101-115 - [c22]Pablo Felipe Leonhart
A Self-adaptive Local Search Coordination in Multimeme Memetic Algorithm for Molecular Docking. ICCS (3) 2019: 145-159 - 2018
- [j15]Jorge Parraga-Alava
A multi-objective gene clustering algorithm guided by apriori biological knowledge with intensification and diversification strategies. BioData Min. 11(1): 16:1-16:22 (2018) - [j14]Leonardo de Lima Correa, Bruno Borguesan, Mathias J. Krause
Three-dimensional protein structure prediction based on memetic algorithms. Comput. Oper. Res. 91: 160-177 (2018) - [j13]Rodrigo Ligabue-Braun
Everyone Is a Protagonist: Residue Conformational Preferences in High-Resolution Protein Structures. J. Comput. Biol. 25(4): 451-465 (2018) - [j12]Leonardo de Lima Correa, Bruno Borguesan
A Memetic Algorithm for 3D Protein Structure Prediction Problem. IEEE ACM Trans. Comput. Biol. Bioinform. 15(3): 690-704 (2018) - [c21]Bruno Borguesan, Pedro Henrique Narloch, Mario Inostroza-Ponta
A Genetic Algorithm Based on Restricted Tournament Selection for the 3D-PSP Problem. CEC 2018: 1-8 - [c20]Leonardo de Lima Correa, Márcio Dorn
A Knowledge-Based Artificial Bee Colony Algorithm for the 3-D Protein Structure Prediction Problem. CEC 2018: 1-8 - [c19]Bruno Iochins Grisci
Microarray Classification and Gene Selection with FS-NEAT. CEC 2018: 1-8 - [c18]Manuel Villalobos-Cid
Performance Comparison of Multi-Objective Local Search Strategies to Infer Phylogenetic Trees. CEC 2018: 1-8 - [c17]Manuel Villalobos-Cid
Understanding the Relationship Between Decision and Objective Space in the Multi-Objective Phylogenetic Inference Problem. CEC 2018: 1-8 - 2017
- [j11]Bruno Grisci
NEAT-FLEX: Predicting the conformational flexibility of amino acids using neuroevolution of augmenting topologies. J. Bioinform. Comput. Biol. 15(3): 1750009:1-1750009:22 (2017) - [j10]Bruno Borguesan
NIAS-Server: Neighbors Influence of Amino acids and Secondary Structures in Proteins. J. Comput. Biol. 24(3): 255-265 (2017) - [c16]Mariana Oliveira, Bruno Borguesan
SADE-SPL: A Self-Adapting Differential Evolution algorithm with a loop Structure Pattern Library for the PSP problem. CEC 2017: 1095-1102 - [c15]Leonardo de Lima Correa, Mario Inostroza-Ponta
An evolutionary multi-agent algorithm to explore the high degree of selectivity in three-dimensional protein structures. CEC 2017: 1111-1118 - [c14]Jorge Parraga-Alava
Using local search strategies to improve the performance of NSGA-II for the Multi-Criteria Minimum Spanning Tree problem. CEC 2017: 1119-1126 - [c13]Bruno Ferreira de Faria Alixandre
D-BRKGA: A Distributed Biased Random-Key Genetic Algorithm. CEC 2017: 1398-1405 - [c12]Benjamin Ruiz-Tagle, Manuel Villalobos-Cid
Evaluating the use of local search strategies for a memetic algorithm for the protein-ligand docking problem. SCCC 2017: 1-12 - 2016
- [c11]Bruno Borguesan, Jonas Bohrer, Mariel Barbachan e Silva, Leonardo de Lima Correa, Márcio Dorn
Improving protein tertiary structure prediction with conformational propensities of amino acid residues. CEC 2016: 9-15 - [c10]Bruno Grisci
Predicting protein structural features with NeuroEvolution of Augmenting Topologies. IJCNN 2016: 873-880 - [c9]Ivan Escobar, Nicolas Hidalgo
Evaluation of a combined energy fitness function for a distributed memetic algorithm to tackle the 3D protein structure prediction problem. SCCC 2016: 1-10 - 2015
- [j9]Bruno Borguesan
APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction. Comput. Biol. Chem. 59: 142-157 (2015) - [c8]Mario Inostroza-Ponta
A Memetic Algorithm for Protein Structure Prediction based on Conformational Preferences of Aminoacid Residues. GECCO (Companion) 2015: 1403-1404 - 2014
- [j8]Márcio Dorn
Three-dimensional protein structure prediction: Methods and computational strategies. Comput. Biol. Chem. 53: 251-276 (2014) - [j7]Márcio Dorn
MOIRAE: A computational strategy to extract and represent structural information from experimental protein templates. Soft Comput. 18(4): 773-795 (2014) - 2013
- [j6]Márcio Dorn
A molecular dynamics and knowledge-based computational strategy to predict native-like structures of polypeptides. Expert Syst. Appl. 40(2): 698-706 (2013) - [j5]Rafael K. de Andrades, Márcio Dorn
A cluster-DEE-based strategy to empower protein design. Expert Syst. Appl. 40(13): 5210-5218 (2013) - [j4]Márcio Dorn
An interval-based algorithm to represent conformational states of experimentally determined polypeptide templates and fast prediction of approximated 3D protein structures. Int. J. Bioinform. Res. Appl. 9(5): 462-486 (2013) - [c7]Márcio Dorn
A knowledge-based genetic algorithm to predict three-dimensional structures of polypeptides. IEEE Congress on Evolutionary Computation 2013: 1233-1240 - 2012
- [j3]Márcio Dorn
A GMDH polynomial neural network-based method to predict approximate three-dimensional structures of polypeptides. Expert Syst. Appl. 39(15): 12268-12279 (2012) - [c6]André L. S. Braga, Janier Arias-Garcia
Hardware implementation of GMDH-type artificial neural networks and its use to predict approximate three-dimensional structures of proteins. ReCoSoC 2012: 1-8 - 2011
- [c5]Márcio Dorn
A hybrid genetic algorithm for the 3-D protein structure prediction problem using a path-relinking strategy. IEEE Congress on Evolutionary Computation 2011: 2709-2716 - [c4]Márcio Dorn
Combining Machine Learning and Optimization Techniques to Determine 3-D Structures of Polypeptides. IJCAI 2011: 2794-2795 - 2010
- [j2]Márcio Dorn
A3N: An artificial neural network n-gram-based method to approximate 3-D polypeptides structure prediction. Expert Syst. Appl. 37(12): 7497-7508 (2010) - [j1]Márcio Dorn
Mining the Protein Data Bank with CReF to predict approximate 3-D structures of polypeptides. Int. J. Data Min. Bioinform. 4(3): 281-299 (2010)
2000 – 2009
- 2008
- [c3]Márcio Dorn
CReF: a central-residue-fragment-based method for predicting approximate 3-D polypeptides structures. SAC 2008: 1261-1267 - [c2]Mariana Luderitz Kolberg
Parallel Verified Linear System Solver for Uncertain Input Data. SBAC-PAD 2008: 89-96 - [c1]Márcio Dorn
A Hybrid Method for the Protein Structure Prediction Problem. BSB 2008: 47-56
Coauthor Index
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