Mario Inostroza-Ponta

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 36

Top Topics

Biological Knowledge

Multidimensional Scaling

Protein Structure

Top Venues

J. Bioinform. Comput. Biol.

Publications

Felipe-Andrés Bello Robles, Manuel Villalobos-Cid, Max Chacón, Mario Inostroza-Ponta
A multi-objective optimisation approach for the linear modelling of cerebral autoregulation system. Biosyst. 241 (2024)
Manuel Villalobos-Cid, Márcio Dorn, Ángela Contreras, Mario Inostroza-Ponta
An evolutionary algorithm based on parsimony for the multiobjective phylogenetic network inference problem. Appl. Soft Comput. 139 (2023)
Nicolás Mariángel, Juan Giglio, Sebastián Aliaga-Rojas, Manuel Villalobos-Cid, Mario Inostroza-Ponta
Evaluating the incorporation of Biological Knowledge in multiobjective clustering of gene expression data. SCCC (2023)
Vicente Rivera-Rebolledo, Manuel Villalobos-Cid, Mario Inostroza-Ponta
Improving solution diversity on NSGA-II for multi-objective clustering problems. SCCC (2022)
Manuel Villalobos-Cid, César Rivera, Eduardo I. Kessi-Pérez, Mario Inostroza-Ponta
A multi-modal algorithm based on an NSGA-II scheme for phylogenetic tree inference. Biosyst. 213 (2022)
José Fernández Goycoolea, Mario Inostroza-Ponta, Manuel Villalobos-Cid, Mauricio Marín
Single-solution based metaheuristic approach to a novel restricted clustering problem. SCCC (2021)
Sebastián Aliaga-Rojas, Manuel Villalobos-Cid, Márcio Dorn, Mario Inostroza-Ponta
A multi-objective approach for the protein structure prediction problem. SCCC (2021)
Jorge Parraga-Alava, Mario Inostroza-Ponta
Influence of the go-based semantic similarity measures in multi-objective gene clustering algorithm performance. J. Bioinform. Comput. Biol. 18 (6) (2020)
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)
César Rivera, Mario Inostroza-Ponta, Manuel Villalobos-Cid
A multimodal multi-objective optimisation approach to deal with the phylogenetic inference problem. CIBCB (2020)
Mario Inostroza-Ponta, Márcio Dorn, Ivan Escobar, Leonardo de Lima Correa, Erika Rosas, Nicolas Hidalgo, Mauricio Marín
Exploring the high selectivity of 3-D protein structures using distributed memetic algorithms. J. Comput. Sci. 41 (2020)
Angelo Carlier González, José Lillo, Mario Inostroza-Ponta, Manuel Villalobos-Cid
Evaluating the categorisation of the public hospitals in Chile according to case-mix complexity: a genetic algorithm approach. SCCC (2020)
Manuel Villalobos-Cid, Francisco Salinas, Mario Inostroza-Ponta
Total evidence or taxonomic congruence? A comparison of methods for combining biological evidence. J. Bioinform. Comput. Biol. 18 (6) (2020)
Juan Giglio, Mario Inostroza-Ponta, Manuel Villalobos-Cid
A multi-objective optimisation evolutionary approach for the Multidimensional Scaling Problem. SCCC (2019)
Manuel Villalobos-Cid, Maximiliano Orellana, Oscar C. Vásquez, Eduardo Pinto-Sothers, Mario Inostroza-Ponta
Dealing with the Balanced Academic Curriculum Problem considering the Chilean Academic Credit Transfer System. SCCC (2019)
Jorge Parraga-Alava, Roberto Acuña Caicedo, José Manuel Gómez, Mario Inostroza-Ponta
An Unsupervised Learning Approach for Automatically to Categorize Potential Suicide Messages in Social Media. SCCC (2019)
Manuel Villalobos-Cid, Márcio Dorn, Rodrigo Ligabue-Braun, Mario Inostroza-Ponta
A Memetic Algorithm Based on an NSGA-II Scheme for Phylogenetic Tree Inference. IEEE Trans. Evol. Comput. 23 (5) (2019)
Manuel Villalobos-Cid, Márcio Dorn, Mario Inostroza-Ponta
Understanding the Relationship Between Decision and Objective Space in the Multi-Objective Phylogenetic Inference Problem. CEC (2018)
Jorge Parraga-Alava, Márcio Dorn, Mario Inostroza-Ponta
A multi-objective gene clustering algorithm guided by apriori biological knowledge with intensification and diversification strategies. BioData Min. 11 (1) (2018)
Manuel Villalobos-Cid, Márcio Dorn, Mario Inostroza-Ponta
Performance Comparison of Multi-Objective Local Search Strategies to Infer Phylogenetic Trees. CEC (2018)
Bruno Borguesan, Pedro Henrique Narloch, Mario Inostroza-Ponta, Márcio Dorn
A Genetic Algorithm Based on Restricted Tournament Selection for the 3D-PSP Problem. CEC (2018)
Leonardo de Lima Correa, Bruno Borguesan, Camilo Farfán, Mario Inostroza-Ponta, Márcio Dorn
A Memetic Algorithm for 3D Protein Structure Prediction Problem. IEEE ACM Trans. Comput. Biol. Bioinform. 15 (3) (2018)
Jorge Parraga-Alava, Gustavo Molina Garzon, Roberth Alcivar Cevallos, Mario Inostroza-Ponta
Unsupervised Pattern Recognition for Geographical Clustering of Seismic Events Post MW 7.8 Ecuador Earthquake. SCCC (2018)
Roberto Sandoval-Soto, Manuel Villalobos-Cid, Mario Inostroza-Ponta
Tackling the bi-objective quadratic assignment problem by characterizing different memory strategies in a memetic algorithm. SCCC (2017)
Manuel Villalobos-Cid, Daniel Vega-Araya, Mario Inostroza-Ponta
Application of different multi-objective decision making techniques in the phylogenetic inference problem. SCCC (2017)
Jorge Parraga-Alava, Márcio Dorn, Mario Inostroza-Ponta
Using local search strategies to improve the performance of NSGA-II for the Multi-Criteria Minimum Spanning Tree problem. CEC (2017)
Benjamin Ruiz-Tagle, Manuel Villalobos-Cid, Márcio Dorn, Mario Inostroza-Ponta
Evaluating the use of local search strategies for a memetic algorithm for the protein-ligand docking problem. SCCC (2017)
Leonardo de Lima Correa, Mario Inostroza-Ponta, Márcio Dorn
An evolutionary multi-agent algorithm to explore the high degree of selectivity in three-dimensional protein structures. CEC (2017)
Bruno Borguesan, Mario Inostroza-Ponta, Márcio Dorn
NIAS-Server: Neighbors Influence of Amino acids and Secondary Structures in Proteins. J. Comput. Biol. 24 (3) (2017)
Jorge Parraga-Alava, Mario Inostroza-Ponta
A Bi-Objective Clustering Algorithm for Gene Expression Data. CLEI Electron. J. 20 (2) (2017)
Manuel Villalobos-Cid, Max Chacón, Pedro Zitko, Mario Inostroza-Ponta
A New Strategy to Evaluate Technical Efficiency in Hospitals Using Homogeneous Groups of Casemix - How to Evaluate When There is Not DRGs? J. Medical Syst. 40 (4) (2016)
Jorge Parraga-Alava, Mario Inostroza-Ponta
A bi-objective model for gene clustering combining expression data and external biological knowledge. CLEI (2016)
Ivan Escobar, Nicolas Hidalgo, Mario Inostroza-Ponta, Mauricio Marín, Erika Rosas, Márcio Dorn
Evaluation of a combined energy fitness function for a distributed memetic algorithm to tackle the 3D protein structure prediction problem. SCCC (2016)
Bruno Borguesan, Mariel Barbachan e Silva, Bruno Grisci, Mario Inostroza-Ponta, Márcio Dorn
APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction. Comput. Biol. Chem. 59 (2015)
Mario Inostroza-Ponta, Camilo Farfán, Márcio Dorn
A Memetic Algorithm for Protein Structure Prediction based on Conformational Preferences of Aminoacid Residues. GECCO (Companion) (2015)
Matthew Harris, Regina Berretta, Mario Inostroza-Ponta, Pablo Moscato
A Memetic Algorithm for the Quadratic Assignment Problem with parallel local search. CEC (2015)
Márcio Dorn, Mario Inostroza-Ponta, Luciana S. Buriol, Hugo Verli
A knowledge-based genetic algorithm to predict three-dimensional structures of polypeptides. IEEE Congress on Evolutionary Computation (2013)
Hugo Meneses, Mario Inostroza-Ponta
Evaluating Memory Schemas in a Memetic Algorithm for the Quadratic Assignment Problem. SCCC (2011)
Ahmed Shamsul Arefin, Mario Inostroza-Ponta, Luke Mathieson, Regina Berretta, Pablo Moscato
Clustering Nodes in Large-Scale Biological Networks Using External Memory Algorithms. ICA3PP (2) (2011)
Mario Inostroza-Ponta, Alexandre Mendes, Regina Berretta, Pablo Moscato
An Integrated QAP-Based Approach to Visualize Patterns of Gene Expression Similarity. ACAL (2007)
Mario Inostroza-Ponta, Regina Berretta, Alexandre Mendes, Pablo Moscato
An automatic graph layout procedure to visualize correlated data. IFIP AI (2006)