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Acuna, M., Eaton, L., Ramirez, N. R., Cifuentes, L., & Llop, E. (2003). Genetic variants of serum butyrylcholinesterase in Chilean Mapuche Indians. Am. J. Phys. Anthropol., 121(1), 81–85.
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Aledo, J. A., Goles, E., Montalva-Medel, M., Montealegre, P., & Valverde, J. C. (2023). Symmetrizable Boolean networks. Inf. Sci., 626, 787–804.
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Allende, C., Sohn, E., & Little, C. (2015). Treelink: data integration, clustering and visualization of phylogenetic trees. BMC Bioinformatics, 16, 6 pp.
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Allende, H., Bravo, D., & Canessa, E. (2010). Robust design in multivariate systems using genetic algorithms. Qual. Quant., 44(2), 315–332.
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Altimiras, F., Uszczynska-Ratajczak, B., Camara, F., Vlasova, A., Palumbo, E., Newhouse, S., et al. (2017). Brain Transcriptome Sequencing of a Natural Model of Alzheimer's Disease. Front. Aging Neurosci., 9, 8 pp.
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Alvarez-Miranda, E., Pereira, J., Torrez-Meruvia H., & Vila, M. (2021). A Hybrid Genetic Algorithm for the Simple Assembly Line Balancing Problem with a Fixed Number of Workstations. Mathematics, 9(17), 2157.
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Asenjo, F. A., & Hojman, S. A. (2022). Airy heat bullets. Eur. Phys. J. Plus., 137(10), 1201.
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Bachoc, F., Porcu, E., Bevilacqua, M., Furrer, R., & Faouzi, T. (2022). Asymptotically equivalent prediction in multivariate geostatistics. Bernoulli, 28(4), 2518–2545.
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Balbontin, C., Hensher, D. A., & Ho, C. (2023). Light commercial vehicles destination choice: Understanding preferences relative to the number of stop and tour-based trip type. Transp. Res. E-Logist. Transp. Rev., 171, 103042.
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Barroso, L., Munoz, F. D., Bezerra, B., Rudnick, H., & Cunha, G. (2021). Zero-Marginal-Cost Electricity Market Designs: Lessons Learned From Hydro Systems in Latin America Might Be Applicable for Decarbonization. IEEE Power Energy Mag., 19(1), 64–73.
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Becker, F., Montealegre, P., Rapaport, I., & Todinca, I. (2020). The Impact Of Locality In The Broadcast Congested Clique Model. SIAM Discret. Math., 34(1), 682–700.
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Bergen, M., & Munoz, F. D. (2018). Quantifying the effects of uncertain climate and environmental policies on investments and carbon emissions: A case study of Chile. Energy Econ., 75, 261–273.
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Besaury, L., Ouddane, B., Pavissich, J. P., Dubrulle-Brunaud, C., Gonzalez, B., & Quillet, L. (2012). Impact of copper on the abundance and diversity of sulfate-reducing prokaryotes in two chilean marine sediments. Mar. Pollut. Bull., 64(10), 2135–2145.
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Bevilacqua, M., Camano-Carrillo, C., & Porcu, E. (2022). Unifying compactly supported and Matern covariance functions in spatial statistics. J. Multivar. Anal., 189, 104949.
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Cáeres, C., Heusser, B., Garnham, A., & Moczko, E. (2023). The Major Hypotheses of Alzheimer's Disease: Related Nanotechnology-Based Approaches for Its Diagnosis and Treatment. Cells, 12(23), 2669.
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Campas, O., Rojas, E., Dumais, J., & Mahadevan, L. (2012). Strategies For Cell Shape Control In Tip-Growing Cells. Am. J. Bot., 99(9), 1577–1582.
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Canessa, E., & Chaigneau, S. (2015). Calibrating Agent-Based Models Using a Genetic Algorithm. Stud. Inform. Control, 24(1), 79–90.
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Canessa, E., & Chaigneau, S. (2017). Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design. Ing. Invest., 37(2), 89–98.
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Canessa, E., Droop, C., & Allende, H. (2012). An improved genetic algorithm for robust design in multivariate systems. Qual. Quant., 46(2), 665–678.
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Canessa, E., Vera, S., & Allende, H. (2012). A new method for estimating missing values for a genetic algorithm used in robust design. Eng. Optimiz., 44(7), 787–800.
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