- Akgundogdu, A., Jennane, R., Aufort, G., Benhamou, C.L. & Ucan, O.N. (2010). 3D image analysis and artificial intelligence for bone disease classification. Journal of Medical Systems, 34(5), 815-828.
- Alexander, D. H., Novembre, J. & Lange, K. (2009). Fast model-based estimation of ancestry in unrelated individuals. Genome research, 19(9), 1655-1664.
- Anonymous.Statical center of Iran (2012). Available from: http: www.amar.org ir/
- Boser, B.E., Guyon, I.M. & Vapnik, V.N. (1992). A training algorithm for optimal margin classifiers. Paper presented at the Proceedings of the fifth annual workshop on Computational learning theory.
- Bridges, M., Heron, E. A., O'Dushlaine, C., Segurado, R., Morris, D., Corvin, A., ... Consortium, I. S. (2011a). Genetic classification of populations using supervised learning. PLoS ONE, 6(5), e14802.
- Bridges, M., Heron, E. A., O'Dushlaine, C., Segurado, R., Morris, D., Corvin, A., ... Consortium, I.S. (2011b). Genetic classification of populations using supervised learning.
- Brown, M. P., Grundy, W. N., Lin, D., Cristianini, N., Sugnet, C. W., Furey, T. S., ... Haussler, D. (2000). Knowledge-based analysis of microarray gene expression data by using support vector machines. Proceedings of the National Academy of Sciences, 97(1), 262-267.
- Buturovic, L., Cohen, S., He, Z., Eggenberger, M., Nacci, D. & Petkovic, D. Supervised Classification of Genetic Sequences for Population Analysis.
- Cavalli-Sforza, L. L. & Feldman, M. W. (2003). The application of molecular genetic approaches to the study of human evolution. nature genetics, 33, 266-275.
- Cortes, C. & Vapnik, V. (1995). Support-vector networks. Machine learning, 20(3), 273-297.
- Epps, C. W., Castillo, J. A., Schmidt-Küntzel, A., du Preez, P., Stuart-Hill, G., Jago, M. & Naidoo, R. (2013). Contrasting historical and recent gene flow among African buffalo herds in the Caprivi Strip of Namibia. Journal of Heredity, ess142.
- Fernández, M. E., Goszczynski, D. E., Lirón, J. P., Villegas-Castagnasso, E. E., Carino, M. H., Ripoli, M. V., ... Giovambattista, G. (2013). Comparison of the effectiveness of microsatellites and SNP panels for genetic identification, traceability and assessment of parentage in an inbred Angus herd. Genetics and molecular biology, 36(2), 185-191.
- Gao, X. & Starmer, J. (2007). Human population structure detection via multilocus genotype clustering. BMC genetics, 8(1), 34.
- Guerard, E., Heyer, E. & Manni, F. (2004). Geographic patterns of (genetic, morphologic, linguistic) variation: how barriers can be detected by using Monmonier's algorithm. Human biology, 76(2), 173-190.
- Guinand, B., Topchy, A., Page, K., Burnham-Curtis, M., Punch, W. & Scribner, K. (2002). Comparisons of likelihood and machine learning methods of individual classification. Journal of Heredity, 93(4), 260-269.
- Gutiérrez, S., Tardaguila, J., Fernández-Novales, J., Diago, M. P. & Scali, M. (2015). Support Vector Machine and Artificial Neural Network Models for the Classification of Grapevine Varieties Using a Portable NIR Spectrophotometer. PLoS ONE, 10(11), e0143197.
- Hand, D. J. (2009). Measuring classifier performance: a coherent alternative to the area under the ROC curve. Machine learning, 77(1), 103-123.
- Hastie, T., Tibshirani, R., Friedman, J. & Franklin, J. (2005). The elements of statistical learning: data mining, inference and prediction. The Mathematical Intelligencer, 27(2), 83-85.
- Hsu, C.-W., Chang, C.-C. & Lin, C.-J. (2003a). A practical guide to support vector classification.
- Hsu, C.-W., Chang, C.-C. & Lin, C.-J. (2003b). A practical guide to support vector classification.
- https://cran.r-project.org/web/packages/e1071/index.html.
- Kohavi, R. (1995). A study of cross-validation and bootstrap for accuracy estimation and model selection. Paper presented at the Ijcai.
- Lao, O., Lu, T.T., Nothnagel, M., Junge, O., Freitag-Wolf, S., Caliebe, A., ... Comas, D. (2008). Correlation between genetic and geographic structure in Europe. Current Biology, 18(16), 1241-1248.
- Larrañaga, P., Calvo, B., Santana, R., Bielza, C., Galdiano, J., Inza, I., ... Pérez, A. (2006). Machine learning in bioinformatics. Briefings in bioinformatics, 7(1), 86-112.
- Limpiti, T., Intarapanich, A., Assawamakin, A., Shaw, P. J., Wangkumhang, P., Piriyapongsa, J., ... Tongsima, S. (2011). Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and structure. BMC bioinformatics, 12(1), 255.
- Lin, B. Z., Sasazaki, S. & Mannen, H. (2010). Genetic diversity and structure in Bos taurus and Bos indicus populations analyzed by SNP markers. Animal science journal, 81(3), 281-289.
- Liu, L., Zhang, D., Liu, H. & Arendt, C. (2013). Robust methods for population stratification in genome wide association studies. BMC bioinformatics, 14(1), 1.
- Ma, J. & Amos, C. I. (2010). Theoretical formulation of principal components analysis to detect and correct for population stratification. PLoS ONE, 5(9), e12510.
- Marchini, J., Cardon, L. R., Phillips, M. S. & Donnelly, P. (2004). The effects of human population structure on large genetic association studies. Nature genetics, 36(5), 512-517.
- McTavish, E. J. & Hillis, D. M. (2014). A genomic approach for distinguishing between recent and ancient admixture as applied to cattle. Journal of Heredity, 105(4), 445-456.
- Naserian, A. A. & Saremi, B. (2010). Water buffalo industry in Iran. Italian Journal of Animal Science, 6(2s), 1404-1405.
- Price, A.L., Zaitlen, N.A., Reich, D. & Patterson, N. (2010). New approaches to population stratification in genome-wide association studies. Nature Reviews Genetics, 11(7), 459-463.
- Saitou, N. & Nei, M. (1987). The neighbor-joining method: a new method for reconstructing phylogenetic trees. Molecular biology and evolution, 4(4), 406-425.
- Stehman, S. V. (1997). Selecting and interpreting measures of thematic classification accuracy. Remote sensing of Environment, 62(1), 77-89.
- Steinwart, I. & Christmann, A. (2008). Support vector machines: Springer Science & Business Media.
- Swets, J. A. (1988). Measuring the accuracy of diagnostic systems. Science, 240(4857), 1285-1293.
- Thomas, D. C. & Witte, J. S. (2002). Point: population stratification: a problem for case-control studies of candidate-gene associations? Cancer Epidemiology Biomarkers & Prevention, 11(6), 505-512.
- Vapnik, V. N. & Vapnik, V. (1998). Statistical learning theory (Vol. 1): Wiley New York.
- Vignal, A., Milan, D., SanCristobal, M. & Eggen, A. (2002). A review on SNP and other types of molecular markers and their use in animal genetics. Genetics Selection Evolution, 34(3), 275-306.
- Wacholder, S., Rothman, N. & Caporaso, N. (2002). Counterpoint: bias from population stratification is not a major threat to the validity of conclusions from epidemiological studies of common polymorphisms and cancer. Cancer Epidemiology Biomarkers & Prevention, 11(6), 513-520.
- Wright, S. (1949). The genetical structure of populations. Annals of eugenics, 15(1), 323-354.
- Wright, S. (1969). Evolution and the genetics of populations: Vol. 2. The theory of gene frequencies.
- Ziv, E. & Burchard, E.G. (2003). Human population structure and genetic association studies. Pharmacogenomics, 4(4), 431-441.
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