Mario Inostroza-Ponta

Reseña

Mario Inostroza Ponta obtiene su maestría el año 2000 en la Universidad de Santiago de Chile y su PhD el año 2008 en la Universidad de Newcastle en Australia. Es miembro del Departamento de Ingeniería Informática de la Universidad de Santiago de Chile desde el año 2002. Además, tiene experiencia de trabajo en la industria en desarrollo e integración de plataformas de aprovisionamiento. Su principal experiencia es en ingeniería en computación o ciencias de la computación, específicamente en las áreas de heurísticas y metaheurísticas, aplicadas a problemas de optimización combinatoria en programación y bioinformática, entre otros.

Grados
Año Grado/Título Institución
2008 PhD Computer Science The University of Newcastle
2000 Magíster en Ingeniería Informática Universidad de Santiago de Chile
1999 Ingeniero Civil en Informática Universidad de Santiago de Chile
1998 Licenciado en Ciencias de la Ingeniería Universidad de Santiago de Chile

Publicaciones en revistas indexadas

  1. Parraga-Alava, J., Dorn, M., Inostroza-Ponta, M. A multi-objective gene clustering algorithm guided by apriori biological knowledge with intensification and diversification strategies (2018) BioData Mining, 11 (1), art. no. 16, DOI: 10.1186/s13040-018-0178-4
  2. Correa, L., Borguesan, B., Farfan, C., Inostroza-Ponta, M., Dorn, M. A memetic algorithm for 3D protein structure prediction problem (2018) IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15 (3), pp. 690-704. DOI: 10.1109/TCBB.2016.2635143
  3. Borguesan, B., Inostroza-Ponta, M., Dorn, M. NIAS-Server: Neighbors Influence of Amino acids and Secondary Structures in Proteins (2017) Journal of Computational Biology, 24 (3), pp. 255-265. DOI: 10.1089/cmb.2016.0074
  4. Villalobos-Cid, M., Chacón, M., Zitko, P., Instroza-Ponta, M. A New Strategy to Evaluate Technical Efficiency in Hospitals Using Homogeneous Groups of Casemix: How to Evaluate When There is Not DRGs? (2016) Journal of Medical Systems, 40 (4), art. no. 103, pp. 1-12. DOI: 10.1007/s10916-016-0458-9
  5. Borguesan, B., E Silva, M.B., Grisci, B., Inostroza-Ponta, M., Dorn, M. APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction (2015) Computational Biology and Chemistry, 59, pp. 142-157. DOI: 10.1016/j.compbiolchem.2015.08.006
  6. Ramírez-Castrillón, M., Mendes, S.D.C., Inostroza-Ponta, M., Valente, P. (GTG)5 MSP-PCR fingerprinting as a technique for discrimination of wine associated yeasts? (2014) PLoS ONE, 9 (8), art. no. e105870. DOI: 10.1371/journal.pone.0105870
  7. Clark, M.B., Johnston, R.L., Inostroza-Ponta, M., Fox, A.H., Fortini, E., Moscato, P., Dinger, M.E., Mattick, J.S. Genome-wide analysis of long noncoding RNA stability (2012) Genome Research, 22 (5), pp. 885-898. DOI: 10.1101/gr.131037.111
  8. Inostroza-Ponta, M., Berretta, R., Moscato, P. QAPgrid: A two level QAP-based approach for large- scale data analysis and visualization (2011) PLoS ONE, 6 (1), art. no. e14468. DOI: 10.1371/journal.pone.0014468
  9. 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. A Transcription Factor Map as Revealed by a Genome- Wide Gene Expression Analysis of Whole-Blood mRNA Transcriptome in Multiple Sclerosis (2010) PLoS ONE, 5 (12), art. no. e14176. DOI: 10.1371/journal.pone.0014176
  10. 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. Is there more than one proctitis syndrome? A revisitation using data from the TROG 96.01 trial (2009) Radiotherapy and Oncology, 90 (3), pp. 400-407. DOI: 10.1016/j.radonc.2008.09.019

Publicaciones en congresos nacionales

  1. O Rojas, M Mendoza, M Marín, M Inostroza-Ponta (2010) Framework de evaluación de crawling focalizado distribuido, Workshop de Sistemas Distribuidos y Paralelismo, (WSDP-JCC 2010). Antofagasta,Chile.
  2. Inostroza-Ponta y P. Moscato (2008), Estudio de robustez del algoritmo de clustering basado engrafos MSTkNN, Encuentro Chileno de Computación, JCC2008. Nov 10-15. Punta Arenas, Chile.
  3. Inostroza, Bastías S., Villanueva M. y Ortiz C. (1999), Metaheurísticas para Coloración de Aristas de Grafos, III Congreso Chileno de Investigación Operativa OPTIMA 99, Arica. Chile.

Seminarios y otras presentaciones

  1. Unsupervised techniques for the analysis of gene expression data, Instituto de Informática, Universidade Federal do Rio Grande so Sul (UFGRS), 28th January 2010, Porto Alegre, Brasil.
  2. Unidad de Bioinformática, Centro de Genómica Nutricional Agroacuícola (CGNA), 7th of January 2010, Temuco, Chile.
  3. A Graph Approach to Visualize Correlated Data. Bioinformatics Student Symposium organized by The Bioinformatics Institute (New Zealand) and The Australian Research Council Centre in Bioinformatics (ACB), July 11 14, 2006, Auckland University, Auckland, New Zealand.
  4. Discovering Shared Information from DNA Sequences and Documents: A Graph Drawing Approach.Poster Presentation, Summer Symposium in Bioinformatics: BioInfoSummer 2004, December 6 10, Australian National University, Canberra, Australia.

Conferencias indexadas

  1. M Villalobos-Cid, M Dorn, M Inostroza-Ponta, Understanding the Relationship Between Decision and Objective Space in the Multi-Objective Phylogenetic Inference Problem (2018) IEEE Congress on Evolutionary Computation (CEC), 1-8. DOI: 10.1109/CEC.2018.8477689
  2. M Villalobos-Cid, M Dorn, M Inostroza-Ponta, Performance Comparison of Multi-Objective Local Search Strategies to Infer Phylogenetic Trees (2018) IEEE Congress on Evolutionary Computation (CEC), 1-8. DOI: 10.1109/CEC.2018.8477666
  3. B Borguesan, PH Narloch, M Inostroza-Ponta, M Dorn, A Genetic Algorithm Based on Restricted Tournament Selection for the 3D-PSP Problem (2018) IEEE Congress on Evolutionary Computation (CEC), 1-8. DOI: 10.1109/CEC.2018.8477721
  4. Sandoval-Soto, R., Villalobos-Cid, M., Inostroza-Ponta, M. Tackling the bi-objective quadratic assignment problem by characterizing different memory strategies in a memetic algorithm (2018) Proceedings – International Conference of the Chilean Computer Science Society, SCCC, 2017-October, pp. 1-12. DOI: 10.1109/SCCC.2017.8405140
  5. Ruiz-Tagle, B., Villalobos-Cid, M., Dorn, M., Inostroza-Ponta, M. Evaluating the use of local search strategies for a memetic algorithm for the protein-ligand docking problem (2018) Proceedings – International Conference of the Chilean Computer Science Society, SCCC, 2017-October, pp. 1-12. DOI: 10.1109/SCCC.2017.8405141
  6. Villalobos-Cid, M., Vega-Araya, D., Inostroza-Ponta, M. Application of different multi-objective decision making techniques in the phylogenetic inference problem (2018) Proceedings – International Conference of the Chilean Computer Science Society, SCCC, 2017-October, pp. 1-9. DOI: 10.1109/SCCC.2017.8405145
  7. De Lima Corrêa, L., Inostroza-Ponta, M., Dorn, M. An evolutionary multi-agent algorithm to explore the high degree of selectivity in three-dimensional protein structures (2017) 2017 IEEE Congress on Evolutionary Computation, CEC 2017 – Proceedings, art. no. 7969431, pp. 1111-1118. DOI: 10.1109/CEC.2017.7969431
  8. Párraga-Álava, J., Dorn, M., Inostroza-Ponta, M. Using local search strategies to improve the performance of NSGA-II for the Multi-Criteria Minimum Spanning Tree problem (2017) 2017 IEEE Congress on Evolutionary Computation, CEC 2017 – Proceedings, art. no. 7969432, pp. 1119-1126. DOI: 10.1109/CEC.2017.7969432
  9. Escobar, I., Hidalgo, N., Inostroza-Ponta, M., Marin, M., Rosas, E., Dorn, M. Evaluation of a combined energy fitness function for a distributed memetic algorithm to tackle the 3D protein structure prediction problem (2017) Proceedings – International Conference of the Chilean Computer Science Society, SCCC, art. no. 7836019. DOI: 10.1109/SCCC.2016.7836019
  10. Parraga-Alava, J., Inostroza-Ponta, M. A bi-objective model for gene clustering combining expression data and external biological knowledge (2017) Proceedings of the 2016 42nd Latin American Computing Conference, CLEI 2016, art. no. 7833327. DOI: 10.1109/CLEI.2016.7833327
  11. Warren, C., Inostroza-Ponta, M., Moscato, P. Using the QAP grid visualization approach for biomarker identification of cell-specific transcriptomic signatures (2017) Methods in Molecular Biology, 1526, pp. 271-297. DOI: 10.1007/978-1-4939-6613-4_16
  12. Harris, M., Berretta, R., Inostroza-Ponta, M., Moscato, P. A Memetic Algorithm for the Quadratic Assignment Problem with parallel local search (2015) 2015 IEEE Congress on Evolutionary Computation, CEC 2015 – Proceedings, art. no. 7256978, pp. 838-845. DOI: 10.1109/CEC.2015.7256978
  13. Inostroza-Ponta, M., Farfán, C., Dorn, M. A memetic algorithm for protein structure prediction based on conformational preferences of aminoacid residues (2015) GECCO 2015 – Companion Publication of the 2015 Genetic and Evolutionary Computation Conference, pp. 1403-1404. DOI: 10.1145/2739482.2764682
  14. Dorn, M., Inostroza-Ponta, M., Buriol, L.S., Verli, H. A knowledge-based genetic algorithm to predict three-dimensional structures of polypeptides (2013) 2013 IEEE Congress on Evolutionary Computation, CEC 2013, art. no. 6557706, pp. 1233-1240. DOI: 10.1109/CEC.2013.6557706
  15. Meneses, H., Inostroza-Ponta, M.Evaluating memory schemas in a memetic algorithm for the quadratic assignment problem (2012) Proceedings – International Conference of the Chilean Computer Science Society, SCCC, pp. 14-18. DOI: 10.1109/SCCC.2011.3
  16. Arefin, A.S., Inostroza-Ponta, M., Mathieson, L., Berretta, R., Moscato, P. Clustering nodes in large-scale biological networks using external memory algorithms (2011) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7017 LNCS (PART 2), pp. 375-386. DOI: 10.1007/978-3-642-24669-2_36
  17. Inostroza-Ponta, M., Mendes, A., Berretta, R., Moscato, P. An integrated QAP-based approach to visualize patterns of gene expression similarity (2007) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4828 LNAI, pp. 156-167. DOI: 10.1007/978-3-540-76931-6_14
  18. Inostroza-Ponta, M., Berretta, R., Mendes, A., Moscato, P. An automatic graph layout procedure to visualize correlated data (2006) IFIP International Federation for Information Processing, 217, pp. 179-188. DOI: 10.1007/978-0-387-34747-9_19

Participación en proyectos

  1. Project STIC-AMSUD cdigo 17-STIC-05 (2017-2018)
    Title: PaDMetBio: Parallel and Distributed Metaheuritics for Structural Bioinformatic
  2. Project: DICYT-USACH (2016-2018) Investigador Principal.
    Title: Metaheurísticas robustas para enfrentar problemas de optimización multiobjetivos en bioinformática
  3. Project CEBIB Centre for biotechnology and bioengineering, Young Associate Resesarcher
    Fondo Basal, 2013, CONICYT.
  4. Project: STIC-AMSUD 13STIC-09 (2013-2014)
    Title: Federated Cloud Computing for Bioinformatics: Infrastructure, Algorithms and Applications.
  5. Project: FONDECYT INICIACION 11121288 (2012-2015)
    Title: Designing and constructing a scalable pipeline of graph-based methods for the analysis of gene expression data.
  6. Project: DICYT-USACH (2009-2010)
    Title: Uso de algoritmos de grafos, optimización combinatorial y bases de datos biológicas para el análisis de datos de expresión genética.