OUR
PUBLICATIONS
Contreras, Á., Villalobos‐Cid, M., Valdés, C., Villarroel, C. A., Castro, F., Farías, I., & Lorca, G. (2025). Obtaining new brewing yeasts using regional Chilean wine yeasts through an adaptive evolution program. Frontiers in Microbiology, 16, 1599904. https://doi.org/10.3389/fmicb.2025.1599904
Chourio-Acevedo, L., Madrid-Muñoz, G., Kri-Amar, F., Román-Cortés, A., Joglar-Campos, C., & Villalobos-Cid, M. (2025). Assessing academic workload in computing engineering programs: A preliminary study. In Revista Digital Educación En Ingeniería (Vol. 20, p. 1-13). https://doi.org/10.26507/rei.v20n39.1297
Tona Peres, I., da Cunha Braga, L., & dos Santos Lourenço Bastos, L., & Villalobos-Cid, M. (2025) Efficiency analysis of healthcare systems in Latin American and Caribbean countries: An application based on data envelopment analysis. In Value in Health Regional Issues (Vol. 46, p. 101075). https://doi.org/10.1016/j.vhri.2024.101075
G. Tobar Carrizo, C.D. González Quintana, R. Atenas, E. Rocuant, C. Quijada, & Villalobos-Cid, M. (2024). Results of the first online survey of the Chilean network of rheumatic patients. Annals of the Rheumatic Diseases, 83 (Supplement 1), 1220–1221. https://doi.org/10.1136/annrheumdis-2024-eular.4034
Bello-Robles, F.-A., Villalobos-Cid, M., Chacón, M., & Inostroza-Ponta, M. (2024). A multi-objective optimisation approach for the linear modelling of cerebral autoregulation system. In BioSystems (Vol. 241, p. 105231). Elsevier BV. https://doi.org/10.1016/j.biosystems.2024.105231.
Vásquez-Salgado, J., L. Figueroa, R., Sotelo, J., & Villalobos-Cid, M. (2024). Biomedical engineering research in Chilean universities - A bibliometric analysis. In IEEE Latin America Transactions (Vol. 22, Issue 4, pp. 339–351). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/tla.2024.10472960.
Kessi-Pérez, E. I., Acuña, E., Bastías, C., Fundora, L., Villalobos-Cid, M., Romero, A., Khaiwal, S., De Chiara, M., Liti, G., Salinas, F., & Martínez, C. (2023). Single nucleotide polymorphisms associated with wine fermentation and adaptation to nitrogen limitation in wild and domesticated yeast strains. In Biological Research (Vol. 56, Issue 1). Springer Science and Business Media LLC. https://doi.org/10.1186/s40659-023-00453-2.
Villalobos-Cid, M., Dorn, M., Contreras, Á., & Inostroza-Ponta, M. (2023). An evolutionary algorithm based on parsimony for the multiobjective phylogenetic network inference problem. In Applied Soft Computing (Vol. 139, p. 110270). Elsevier BV. https://doi.org/10.1016/j.asoc.2023.110270.
Villalobos-Cid, M., Rivera, C., Kessi-Pérez, E. I., & Inostroza-Ponta, M. (2022). A multi-modal algorithm based on an NSGA-II scheme for phylogenetic tree inference. In Biosystems (Vol. 213, p. 104606). Elsevier BV. https://doi.org/10.1016/j.biosystems.2022.104606.
Parraga-Alava, J., & Inostroza-Ponta, M. (2020). Influence of the GO-based semantic similarity measures in multi-objective gene clustering algorithm performance. Journal of Bioinformatics and Computational Biology, 18(06), 2050038. https://doi.org/10.1142/S0219720020500389
Villalobos-Cid, M., Salinas, F., & Inostroza-Ponta, M. (2020). Total evidence or taxonomic congruence? A comparison of methods for combining biological evidence. In Journal of Bioinformatics and Computational Biology (Vol. 18, Issue 06, p. 2050040). World Scientific Pub Co Pte Ltd. https://doi.org/10.1142/s0219720020500407.
Inostroza-Ponta, M., Dorn, M., Escobar, I., de Lima Correa, L., Rosas, E., Hidalgo, N., & Marín, M. (2020). Exploring the high selectivity of 3-D protein structures using distributed memetic algorithms. Journal of Computational Science, 41, 101087. https://doi.org/10.1016/j.jocs.2020.101087
Román, J. and González, D. and Inostroza, M. and Mahn, A., Molecular Modeling of Epithiospecifier and Nitrile-Specifier Proteins of Broccoli and Their Interaction with Aglycones, Molecules, Volume 25, number 4, 2020, doi.org/10.3390/molecules25040772.
Villalobos-Cid, M., Salinas, F., Kessi-Pérez, E. I., De Chiara, M., Liti, M., Inostroza-Ponta, M., Martínez, C. Comparison of phylogenetic tree topologies for nitrogen associated genes partially reconstruct the evolutionary history of Saccharomyces cerevisiae, Microorganisms 2020, 8, 32 doi:10.3390/microorganisms8010032.
Villalobos-Cid, M., Salinas, F., Kessi-Pérez, E. I., De Chiara, M., Liti, G., Inostroza-Ponta, M., & Martínez, C. (2019). Comparison of Phylogenetic Tree Topologies for Nitrogen Associated Genes Partially Reconstruct the Evolutionary History of Saccharomyces cerevisiae. In Microorganisms (Vol. 8, Issue 1, p. 32). MDPI AG. https://doi.org/10.3390/microorganisms8010032.
Villalobos-Cid, M., Dorn, M., Ligabue-Braun, R., & Inostroza-Ponta, M. (2019). A Memetic Algorithm Based on an NSGA-II Scheme for Phylogenetic Tree Inference. In IEEE Transactions on Evolutionary Computation (Vol. 23, Issue 5, pp. 776–787). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/tevc.2018.2883888.
Correa, L., Borguesan, B., Farfan, C., Inostroza-Ponta, M., & Dorn, M. (2018). A memetic algorithm for 3D protein structure prediction problem. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15(2), 690–704. https://doi.org/10.1109/TCBB.2016.2635143
Párraga-Alava, J., Dorn, M., & Inostroza-Ponta, M. (2018). A multi-objective gene clustering algorithm guided by apriori biological knowledge with intensification and diversification strategies. BioData Mining, 11, Artículo 19. https://doi.org/10.1186/s13040-018-0178-4
Warren, C., Inostroza-Ponta, M., & Moscato, P. (2017). Using the QAP grid visualization approach for biomarker identification of cell-specific transcriptomic signatures. In Methods in Molecular Biology (Vol. 1526, pp. 271–297). Springer. https://doi.org/10.1007/978-1-4939-6613-4_16
Borguesan, B., Inostroza-Ponta, M., & Dorn, M. (2017). NIAS-Server: Neighbors Influence of Amino acids and Secondary Structures in Proteins. Journal of Computational Biology, 24(3), 255–265. https://doi.org/10.1089/cmb.2016.0074
Villalobos-Cid, M., Chacón-Pacheco, M., Zitko-Melo, P., & Inostroza-Ponta, M. (2016). A New Strategy to Evaluate Technical Efficiency in Hospitals Using Homogeneous Groups of Casemix. In Journal of Medical Systems (Vol. 40, Issue 4). Springer Science and Business Media LLC. https://doi.org/10.1007/s10916-016-0458-9.
Borguesan, B., E Silva, M. B., Grisci, B., Inostroza-Ponta, M., & Dorn, M. (2015). APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction. Computational Biology and Chemistry, 59, 142–157. https://doi.org/10.1016/j.compbiolchem.2015.08.006
Ramírez-Castrillón, M., Mendes, S. D. C., Inostroza-Ponta, M., & Valente, P. (2014). (GTG)5 MSP-PCR fingerprinting as a technique for discrimination of wine associated yeasts? PLoS ONE, 9(8), Artículo e105870. https://doi.org/10.1371/journal.pone.0105870
Chabert, S., Villalobos, M., Ulloa, P., Salas, R., Tejos, C., San Martin, S., & Pereda, J. (2012). Quantitative description of the morphology and ossification center in the axial skeleton of 20‐week gestation formalin‐fixed human fetuses using magnetic resonance images. In Prenatal Diagnosis (Vol. 32, Issue 3, pp. 252–258). Wiley. https://doi.org/10.1002/pd.2942.
Clark, M. B., Johnston, R. L., Inostroza-Ponta, M., Fox, A. H., Fortini, E., Moscato, P., Dinger, M. E., & Mattick, J. S. (2012). Genome-wide analysis of long noncoding RNA stability. Genome Research, 22(5), 885–898. https://doi.org/10.1101/gr.131037.111
Arefin, A. S., Inostroza-Ponta, M., Mathieson, L., Berretta, R., & Moscato, P. (2011). Clustering nodes in large-scale biological networks using external memory algorithms. In Lecture Notes in Computer Science (Vol. 7017 LNCS, pp. 375–386). Springer. https://doi.org/10.1007/978-3-642-24669-2_36
Inostroza-Ponta, M., Berretta, R., & Moscato, P. (2011). QAPgrid: A two level QAP-based approach for large-scale data analysis and visualization. PLoS ONE, 6(1), Artículo e14468. https://doi.org/10.1371/journal.pone.0014468
Riveros, C., Mellor, D., Gandhi, K. S., McKay, F. C., Cox, M. B., Berretta, R., Vaezpour, S. Y., Inostroza-Ponta, M., Broadley, S. A., Heard, R. N., Vucic, S., Stewart, G. J., Williams, D. W., Scott, R. J., Lechner-Scott, J., Booth, D. R., & Moscato, P. (2010). A Transcription Factor Map as Revealed by a Genome-Wide Gene Expression Analysis of Whole-Blood mRNA Transcriptome in Multiple Sclerosis. PLoS ONE, 5(12), Artículo e14176. https://doi.org/10.1371/journal.pone.0014176
Capp, A., Inostroza-Ponta, M., Bill, D., Moscato, P., Lai, C., Christie, D., Lamb, D., Turner, S., Joseph, D., Matthews, J., Atkinson, C., North, J., Poulsen, M., Spry, N. A., Tai, K.-H., Wynne, C., Duchesne, G., Steigler, A., & Denham, J. W. (2009). Is there more than one proctitis syndrome? A revisitation using data from the TROG 96.01 trial. Radiotherapy and Oncology, 90(3), 400–407. https://doi.org/10.1016/j.radonc.2008.09.019
Inostroza-Ponta, M., Mendes, A., Berretta, R., & Moscato, P. (2007). An integrated QAP-based approach to visualize patterns of gene expression similarity. In Lecture Notes in Computer Science (Vol. 4828 LNAI, pp. 156–167). Springer. https://doi.org/10.1007/978-3-540-76931-6_14
Inostroza-Ponta, M., Berretta, R., Mendes, A., & Moscato, P. (2006). An automatic graph layout procedure to visualize correlated data. IFIP International Federation for Information Processing, 217, 179–188. https://doi.org/10.1007/978-0-387-34747-9_19
Pinacho, P., Solar, M., Inostroza, M., & Muñoz, R. (2004). Using Genetic Algorithms and Tabu search parallel models to solve the scheduling problem. IFIP Advances in Information and Communication Technology, 154, 343–357. Springer
Troncoso, N., Rojo-González, R. Villalobos-Cid, M., Vásquez, O. C, Chavez. H. Economic decision-making tool for distributed solar photovoltaic panels and storage: The case of Chile. Energy Procedia 159:388 - 393, March 2019. DOI: 10.1016/j.egypro.2018.12.071.
Giglio, J., Inostroza-Ponta, M., Villalobos-Cid, M. A multi-objective optimisation evolutionary approach for the Multidimensional Scaling Problem (2019) Proceedings - International Conference of the Chilean Computer Science Society, SCCC, 2019-November, doi:10.1109/SCCC49216.2019.8966433.
Parraga-Alava, J., Caicedo, R.A., Gomez, J.M., Inostroza-Ponta, M. An Unsupervised Learning Approach for Automatically to Categorize Potential Suicide Messages in Social Media (2019) Proceedings - International Conference of the Chilean Computer Science Society, SCCC, 2019-November, doi:10.1109/SCCC49216.2019.8966443.
Villalobos-Cid, M., Orellana, M., Vasquez, O.C., Pinto-Sothers, E., Inostroza-Ponta, M. Dealing with the Balanced Academic Curriculum Problem considering the Chilean Academic Credit Transfer System (2019) Proceedings - International Conference of the Chilean Computer Science Society, SCCC, 2019-November, .doi:10.1109/SCCC49216.2019.8966411.
Manuel Villalobos-Cid, M arcio Dorn, Mario Inostroza-Ponta (2018) Understanding the Relationship Between Decision and Objective Space in the Multi-Objective Phylogenetic Inference Problem, 2018 IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, pp. 1-8.
M. Villalobos-Cid, M. Dorn and M. Inostroza-Ponta (2018) Performance Comparison of Multi-Objective Local Search Strategies to Infer Phylogenetic Trees, 2018 IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, pp. 1-8.
B. Borguesan, P. H. Narloch, M. Inostroza-Ponta and M. Dorn, (2018) A Genetic Algorithm Based on Restricted Tournament Selection for the 3D-PSP Problem, 2018 IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, pp. 1-8.
J. Parraga-Alava, G. M. Garz on, R. Alc var Cevallos and M. Inostroza-Ponta (2018) Unsupervised Pattern Recognition for Geographical Clustering of Seismic Events Post MW 7.8 Ecuador Earthquake, 2018 37th International Conference of the Chilean Computer Science Society (SCCC), Santiago, Chile, pp. 1-8.
M. Villalobos-Cid, D. Vega-Araya and M. Inostroza-Ponta, (2017) Application of different multiobjective decision making techniques in the phylogenetic inference problem, 2017 36th International Conference of the Chilean Computer Science Society (SCCC), Arica, pp. 1-9.
R. Sandoval-Soto, M. Villalobos-Cid and M. Inostroza-Ponta, (2017) Tackling the bi-objective quadratic assignment problem by characterizing different memory strategies in a memetic algorithm, 2017 36th International Conference of the Chilean Computer Science Society (SCCC), Arica, pp. 1-12.
B. Ruiz-Tagle, M. Villalobos-Cid, M. Dorn and M. Inostroza-Ponta, (2017) Evaluating the use of local search strategies for a memetic algorithm for the protein-ligand docking problem, 2017 36th International Conference of the Chilean Computer Science Society (SCCC), Arica, 2017, pp. 1-12.
J. P arraga- Alava, M. Dorn and M. Inostroza-Ponta, (2017) Using local search strategies to improve the performance of NSGA-II for the Multi-Criteria Minimum Spanning Tree problem, 2017 IEEE Congress on Evolutionary Computation (CEC), San Sebastian, 2017, pp. 1119-1126.
L. de Lima Correa, M. Inostroza-Ponta and M. Dorn, (2017) An evolutionary multi-agent algorithm to explore the high degree of selectivity in three-dimensional protein structures, 2017 IEEE Congress on Evolutionary Computation (CEC), San Sebastian, 2017, pp. 1111-1118.
Parraga- Alava J., Inostroza-Ponta M. (2016). A bi-objective model for gene clustering combining expression data and external biological knowledge. CLEI 2016: 1-12.
Escobar I., Hidalgo N., Inostroza-Ponta M., Mar n M., Rosas E. , Dorn M. (2016) Evaluation of a combined energy tness function for a distributed memetic algorithm to tackle the 3D protein structure prediction problem. SCCC 2016: 1-10.
Mario Inostroza-Ponta, Camilo Farf an, M arcio Dorn. (2015) A Memetic Algorithm for Protein Structure Prediction based on Conformational Preferences of Aminoacid Residues. GECCO (Companion) 2015: 1403-1404.
Harris, Matthew; Berretta, Regina; Inostroza-Ponta, Mario; Moscato, Pablo. (2015) A memetic algorithm for the quadratic assignment problem with parallel local search. In: 2015 IEEE Congress on Evolutionary Computation (CEC), 2015, Sendai. 2015 IEEE Congress on Evolutionary Computation (CEC), 2015. p. 838-845.
Dorn, M.; Inostroza-Ponta, M.; Buriol, L.S.; Verli, H. (2013), A knowledge-based genetic algorithm to predict three-dimensional structures of polypeptides, Evolutionary Computation (CEC), 2013 IEEE Congress on, vol., no., pp.1233,1240, 20-23 June 2013. doi: 10.1109/CEC.2013.6557706
Ahmed Shamsul Are n; Inostroza-Ponta, Mario; Luke Mathieson; Berretta, R; Moscato, Pablo (2011) Clustering Nodes in Large-Scale Biological Networks Using External Memory Algorithms. Lecture Notes in Computer Science, v. 7017, p. 375-386. doi:10.1007/978-3-642-24669-2 36
Meneses, H.; Inostroza-Ponta, M., (2011) Evaluating Memory Schemas in a Memetic Algorithm for the Quadratic Assignment Problem, Computer Science Society (SCCC), 2011 30th International Conference of the Chilean , vol., no., pp.14,18, 9-11 Nov. 2011. doi: 10.1109/SCCC.2011.3
M. Inostroza-Ponta, A. Mendes, R. Berretta and P. Moscato. (2007) An integrated QAPbased approach to visualize patterns of gene expression similarity. ACAL 2007 C The Third Australian Conference on Arti cial Life. Lecture Notes in Artificial Intelligence, vol 4828, pp 156-167.
M. Inostroza-Ponta, R. Berretta, A. Mendes, and P. Moscato (2006), An automatic graph layout procedure to visualize correlated data. IFIP 19th World Computer Congress. In Artificial Intelligence in Theory and Practice ser. IFIP International Federation for Information Processing, M. Bramer, Ed., vol. 217. Springer, pp. 179-188.
M. Solar and M. Inostroza (2004), A Scheduling Algorithm to Optimize Real-World Applications. ICDCSW 04: Proceedings of the 24th International Conference on Distributed Computing Systems Workshops-W7: EC (ICDCSW04). IEEE Computer Society, pp. 858-862.
Master thesis - Metaheurística basada en el algoritmo NSGA-II para el problema de predicción de la estructura terciaria de proteínas. Aliaga, S. (2020)
Graduate thesis - Algoritmo genérico para el problema de escalamiento multidimensional multi-objetivo. Giglio, J. (2019)
Graduate thesis - Caracterización de la clasificación de los establecimientos públicos de salud en Chile según complejidad mediante la identificación de variables asociadas a casuística hospitalaria. Carlier-González, Á. (2019)
Graduate thesis - Método de clustering multi-objetivo para el análisis de datos de expresión génica. Villagrán, A. (2017)
Phd thesis - Clustering difuso multi-objetivo de genes basado en información biológica externa y datos de expresión génica. Párraga-Álava, J. (2017)
Phd thesis - Inferencia filogenética multi-objetivo considerando fenómenos reticulares. Villalobos-Cid, M. (2017)
Master thesis - Metaheurística basada en conocimiento para el problema de docking molecular. Ruiz-Tagle, B. (2017)
Master thesis - Algoritmo memético para el problema de asignación cuadrática Bi-Objetivo. Sandoval, R. (2017)
Graduate thesis - Aplicación móvil para apoyar la comunicación entre apoderados y transportistas escolares. Vergara, A. (2017)
Master thesis - Algoritmo memético para problema de docking de proteina rígida y ligando flexible. González, F. (2016)
Graduate thesis - Algoritmo basado en GPU para apoyar el diseño de primers con enzimas de restricción para clonación molecular. Moreno, C. (2016)
Master thesis - Algoritmo de agrupamiento para datos de expresión génica de RNA-Seg con la incorporación de anotaciones biológicas. Cornejo C. (2015)
Graduate thesis - Construcción de un framework para pipeline de aplicaciones de bioinformática. Figueroa, A. (2014)
Graduate thesis - Algoritmo memético para el problema de predicción de la estructura tridimensional de una proteína. Farfán-Pérez, C. (2014)
Master thesis - Incorporación de anotaciones géneticas en el algoritmo de agrupamiento MST-KNN. Pavéz-Sandoval, D. (2013)
Master thesis - Resolución de situaciones de Ko utilizando heurísticas en Montecarlo Go. Acosta, C. (2012)
Graduate thesis - Algoritmo híbrido para el problema de visualización de datos. Bustamante, V. (2011)
Pérez-Cáceres, J., Lillo-Vidal, J., Peres, I. T., & Villalobos-Cid, M. (2024). Impact of the DRG System on Technical Efficiency: A Case Study of Chilean High-Complexity Hospitals. In 2024 43rd International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–8). 2024 43rd International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc63879.2024.10767610
González-Capot, F., Chourio-Acevedo, L., Vásquez, O. C., & Villalobos-Cid, M. (2024). Optimising Planned Academic Workload Distribution: A Multiobjective Approach for the Balanced Academic Curriculum Problem. In 2024 43rd International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–8). 2024 43rd International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc63879.2024.10767644.
Cubillos-Chaparro, J., Dorn, M., Villalobos-Cid, M., & Inostroza-Ponta, M. (2024). A Multiobjective Evolutionary Algorithm for Colon Cancer Biomarkers Identification on Gene Expression Data. In 2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) (pp. 1–8). 2024 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE. https://doi.org/10.1109/cibcb58642.2024.10702102.
Goycoolea, J. F., Quiroz, J., Villalobos-Cid, M., Inostroza-Ponta, M., & Chávez, H. (2023). A Differential Evolution Approach for Reduced Order Frequency Response Models Identification. In 2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) (pp. 1–6). 2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON). IEEE. https://doi.org/10.1109/chilecon60335.2023.10418722.
Mariángel, N., Giglio, J., Aliaga-Rojas, S., Villalobos-Cid, M., & Inostroza-Ponta, M. (2023). Evaluating the incorporation of Biological Knowledge in multiobjective clustering of gene expression data. In 2023 42nd IEEE International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–8). 2023 42nd IEEE International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc59417.2023.10315704.
Rivera-Rebolledo, V., Villalobos-Cid, M., & Inostroza-Ponta, M. (2022). Improving solution diversity on NSGA-II for multi-objective clustering problems. In 2022 41st International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–8). 2022 41st International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc57464.2022.10000384
Aliaga-Rojas, S., Villalobos-Cid, M., Dorn, M., & Inostroza-Ponta, M. (2021). A multi-objective approach for the protein structure prediction problem. In 2021 40th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–8). 2021 40th International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc54552.2021.9650383.
Goycoolea, J. F., Inostroza-Ponta, M., Villalobos-Cid, M., & Marin, M. (2021). Single-solution based metaheuristic approach to a novel restricted clustering problem. In 2021 40th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–7). 2021 40th International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc54552.2021.9650429.
Giglio, J., Gaete-Lucero, G., & Villalobos-Cid, M. (2021). Classification of Chileans public hospitals based on healthcare production using clustering techniques. In 2021 40th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–8). 2021 40th International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc54552.2021.9650434.
Medina, L. E., Villalobos-Cid, M., Alvarez, A., & Chana-Cuevas, P. (2020). Design of a low-cost neuromuscular blockade monitoring device. In 2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) (pp. 1–7). 2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS). IEEE. https://doi.org/10.1109/iciibms50712.2020.9336398
Huallcca, L., Madrid, G., Mellado, J., Vega-Araya, D., & Villalobos-Cid, M. (2020). An informatics tool for class-to-class planning and academic-load evaluation. In 2020 39th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–5). 2020 39th International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc51225.2020.9281221.
Gonzalez, A. C., Lillo, J., Inostroza-Ponta, M., & Villalobos-Cid, M. (2020). Evaluating the categorisation of the public hospitals in Chile according to case-mix complexity: a genetic algorithm approach. In 2020 39th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–9). 2020 39th International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc51225.2020.9281282.
Troncoso, N., Rojo-Gonzalez, L., Vasquez, O. C., Acuna, R., Chavez, H., & Villalobos-Cid, M. (2020). Photovoltaic and Energy Storage Sizing Algorithm for the Chilean Distribution Tariff. In 2020 39th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–5). 2020 39th International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc51225.2020.9281205.
Rivera, C., Inostroza-Ponta, M., & Villalobos-Cid, M. (2020). A multimodal multi-objective optimisation approach to deal with the phylogenetic inference problem. In 2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) (pp. 1–7). 2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE. https://doi.org/10.1109/cibcb48159.2020.9277700.
Correa, L., Arantes, L., Sens, P., Inostroza-Ponta, M., & Dorn, M. (2020). A dynamic evolutionary multi-agent system to predict the 3D structure of proteins. En 2020 IEEE Congress on Evolutionary Computation (CEC 2020). IEEE. https://doi.org/10.1109/CEC48606.2020.9185761
Villalobos-Cid, M., Orellana, M., Vasquez, O. C., Pinto-Sothers, E., & Inostroza-Ponta, M. (2019). Dealing with the Balanced Academic Curriculum Problem considering the Chilean Academic Credit Transfer System. In 2019 38th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–7). 2019 38th International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc49216.2019.8966411
Giglio, J., Inostroza-Ponta, M., & Villalobos-Cid, M. (2019). A multi-objective optimisation evolutionary approach for the Multidimensional Scaling Problem. In 2019 38th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–8). 2019 38th International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc49216.2019.8966433.
Troncoso, N., Rojo-González, L., Villalobos, M., Vásquez, Ó. C., & Chávez, H. (2019). Economic decision-making tool for distributed solar photovoltaic panels and storage: The case of Chile. In Energy Procedia (Vol. 159, pp. 388–393). Elsevier BV. https://doi.org/10.1016/j.egypro.2018.12.071.
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