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Volumn 185, Issue 4, 2010, Pages 1463-1475

Graph-based data selection for the construction of genomic prediction models

Author keywords

[No Author keywords available]

Indexed keywords

MOLECULAR MARKER;

EID: 78751638903     PISSN: 00166731     EISSN: 00166731     Source Type: Journal    
DOI: 10.1534/genetics.110.116426     Document Type: Article
Times cited : (15)

References (40)
  • 2
    • 0141668007 scopus 로고    scopus 로고
    • Reactive local search for the maximum clique problem
    • BATTITI, R., and M. PROTASI, 2001 Reactive local search for the maximum clique problem. Algorithmica 29: 610-637.
    • (2001) Algorithmica , vol.29 , pp. 610-637
    • Battiti, R.1    Protasi, M.2
  • 3
    • 0028141065 scopus 로고
    • Prediction of maize single-cross performance using RFLPs and information from related hybrids
    • BERNARDO, R., 1994 Prediction of maize single-cross performance using RFLPs and information from related hybrids. Crop Sci. 34: 20-25.
    • (1994) Crop Sci. , vol.34 , pp. 20-25
    • Bernardo, R.1
  • 4
    • 0029157899 scopus 로고
    • Genetic models for predicting maize single-cross performance in unbalanced yield trial data
    • BERNARDO, R., 1995 Genetic models for predicting maize single-cross performance in unbalanced yield trial data. Crop Sci. 35: 141-147.
    • (1995) Crop Sci. , vol.35 , pp. 141-147
    • Bernardo, R.1
  • 5
    • 0029903591 scopus 로고    scopus 로고
    • Best linear unbiased prediction of the performance of crosses between untested maize inbreds
    • BERNARDO, R., 1996 Best linear unbiased prediction of the performance of crosses between untested maize inbreds. Crop Sci. 36: 50-56.
    • (1996) Crop Sci. , vol.36 , pp. 50-56
    • Bernardo, R.1
  • 6
    • 54949113665 scopus 로고    scopus 로고
    • Molecular markers and selection for complex traits in plants: Learning from the last 20 years
    • BERNARDO, R., 2008 Molecular markers and selection for complex traits in plants: learning from the last 20 years. Crop Sci. 48: 1649-1664.
    • (2008) Crop Sci. , vol.48 , pp. 1649-1664
    • Bernardo, R.1
  • 7
    • 0002590155 scopus 로고    scopus 로고
    • The maximum clique problem
    • edited by D.-Z. DU and P. M. PARDALOS. Kluwer Academic, Dordrecht, The Netherlands
    • BOMZE, M., M. BUDINICH, P. PARDALOS and M. PELILLO, 1999 The maximum clique problem, pp. 1-74 in Handbook of Combinatorial Optimization, Supplement Vol. A, edited by D.-Z. DU and P. M. PARDALOS. Kluwer Academic, Dordrecht, The Netherlands.
    • (1999) Handbook of Combinatorial Optimization , vol.A , Issue.SUPPL. , pp. 1-74
    • Bomze, M.1    Budinich, M.2    Pardalos, P.3    Pelillo, M.4
  • 8
    • 0018456690 scopus 로고
    • New methods to color the vertices of a graph
    • BRÉLAZ, D., 1979 New methods to color the vertices of a graph. Commun. Assoc. Comput. Mach. 22: 251-256.
    • (1979) Commun. Assoc. Comput. Mach. , vol.22 , pp. 251-256
    • Brélaz, D.1
  • 9
    • 0038545795 scopus 로고    scopus 로고
    • Planning incomplete block experiments when treatments are genetically related
    • BUENO FILHO, S., and S. G. GILMOUR, 2003 Planning incomplete block experiments when treatments are genetically related. Biometrics 59: 375-381.
    • (2003) Biometrics , vol.59 , pp. 375-381
    • Bueno Filho, S.1    Gilmour, S.G.2
  • 10
    • 0025521978 scopus 로고
    • An exact algorithm for the maximum clique problem
    • CARRAGHAN, R., and P. M. PARDALOS, 1990 An exact algorithm for the maximum clique problem. Oper. Res. Lett. 9: 375-382.
    • (1990) Oper. Res. Lett. , vol.9 , pp. 375-382
    • Carraghan, R.1    Pardalos, P.M.2
  • 11
    • 1342298478 scopus 로고
    • On the C-matrix in design of experiments
    • CHAKRABARTI, M. C., 1964 On the C-matrix in design of experiments. J. Indian. Statist. Assoc. 1: 8-23.
    • (1964) J. Indian. Statist. Assoc. , vol.1 , pp. 8-23
    • Chakrabarti, M.C.1
  • 12
    • 65549085067 scopus 로고    scopus 로고
    • Power-law distributions in empirical data
    • CLAUSET, A., C. R. SHALIZI and M. E. J. NEWMAN, 2009 Power-law distributions in empirical data. SIAM Rev. 51: 661-703.
    • (2009) SIAM Rev. , vol.51 , pp. 661-703
    • Clauset, A.1    Shalizi, C.R.2    Newman, M.E.J.3
  • 13
    • 0347540951 scopus 로고    scopus 로고
    • Algorithms for computing the min-transitive closure and associated partition tree of a symmetric fuzzy relation
    • DE MEYER, H., H. NAESSENS and B. DE BAETS, 2004 Algorithms for computing the min-transitive closure and associated partition tree of a symmetric fuzzy relation. Eur. J. Oper. Res. 155: 226-238.
    • (2004) Eur. J. Oper. Res. , vol.155 , pp. 226-238
    • De Meyer, H.1    Naessens, H.2    De Baets, B.3
  • 14
    • 0025699780 scopus 로고
    • The discrete p-dispersion problem
    • ERKUT, E., 1990 The discrete p-dispersion problem. Eur. J. Oper. Res. 46: 48-60.
    • (1990) Eur. J. Oper. Res. , vol.46 , pp. 48-60
    • Erkut, E.1
  • 18
    • 45849117254 scopus 로고    scopus 로고
    • Reproducing kernel Hilbert spaces regression methods for genomic assisted prediction of quantitative traits
    • GIANOLA, D., and J. B. C. H. M. VAN KAAM, 2008 Reproducing kernel Hilbert spaces regression methods for genomic assisted prediction of quantitative traits. Genetics 178: 2289-2303.
    • (2008) Genetics , vol.178 , pp. 2289-2303
    • Gianola, D.1    Van Kaam, J.B.C.H.M.2
  • 20
    • 0642270493 scopus 로고
    • A note on connectedness of block designs
    • HEILIGERS, B., 1991 A note on connectedness of block designs. Metrika 38: 377-381.
    • (1991) Metrika , vol.38 , pp. 377-381
    • Heiligers, B.1
  • 21
    • 0016704147 scopus 로고
    • Best linear unbiased estimation and prediction under a selection model
    • HENDERSON, C. R., 1975 Best linear unbiased estimation and prediction under a selection model. Biometrics 31: 423-447.
    • (1975) Biometrics , vol.31 , pp. 423-447
    • Henderson, C.R.1
  • 24
    • 0027665171 scopus 로고
    • Considerations on genetic connectedness between management units under an animal model
    • KENNEDY, B., and D. TRUS, 1993 Considerations on genetic connectedness between management units under an animal model. J. Anim. Sci. 71: 2341-2352.
    • (1993) J. Anim. Sci. , vol.71 , pp. 2341-2352
    • Kennedy, B.1    Trus, D.2
  • 25
    • 0027145692 scopus 로고
    • Precision and information in linear models of genetic evaluation
    • LALOÉ, D., 1993 Precision and information in linear models of genetic evaluation. Genet. Sel. Evol. 25: 557-576.
    • (1993) Genet. Sel. Evol. , vol.25 , pp. 557-576
    • Laloé, D.1
  • 26
    • 0002735552 scopus 로고    scopus 로고
    • Considerations about measures of precision and connection in mixed linear models of genetic evaluation
    • LALOÉ, D., F. PHOCAS and F. MÉNISSIER, 1996 Considerations about measures of precision and connection in mixed linear models of genetic evaluation. Genet. Sel. Evol. 28: 359-378.
    • (1996) Genet. Sel. Evol. , vol.28 , pp. 359-378
    • Laloé, D.1    Phocas, F.2    Ménissier, F.3
  • 28
    • 35248862454 scopus 로고    scopus 로고
    • Support vector machine regression for the prediction of maize hybrid performance
    • MAENHOUT, S., B. DE BAETS, G. HAESAERT and E. VAN BOCKSTAELE, 2007 Support vector machine regression for the prediction of maize hybrid performance. Theor. Appl. Genet. 115: 1003-1013.
    • (2007) Theor. Appl. Genet. , vol.115 , pp. 1003-1013
    • Maenhout, S.1    De Baets, B.2    Haesaert, G.3    Van Bockstaele, E.4
  • 29
    • 42149153863 scopus 로고    scopus 로고
    • Marker-based screening of maize inbred lines using support vector machine regression
    • MAENHOUT, S., B. DE BAETS, G. HAESAERT and E. VAN BOCKSTAELE, 2008 Marker-based screening of maize inbred lines using support vector machine regression. Euphytica 161: 123-131.
    • (2008) Euphytica , vol.161 , pp. 123-131
    • Maenhout, S.1    De Baets, B.2    Haesaert, G.3    Van Bockstaele, E.4
  • 30
    • 64249167993 scopus 로고    scopus 로고
    • Marker-based estimation of the coefficient of coancestry in hybrid breeding programmes
    • MAENHOUT, S., B. DE BAETS and G. HAESAERT, 2009 Marker-based estimation of the coefficient of coancestry in hybrid breeding programmes. Theor. Appl. Genet. 118: 1181-1192.
    • (2009) Theor. Appl. Genet. , vol.118 , pp. 1181-1192
    • Maenhout, S.1    De Baets, B.2    Haesaert, G.3
  • 31
    • 75849127046 scopus 로고    scopus 로고
    • Prediction of maize single-cross hybrid performance: Support vector machine regression versus best linear prediction
    • MAENHOUT, S., B. DE BAETS and G. HAESAERT, 2010 Prediction of maize single-cross hybrid performance: support vector machine regression versus best linear prediction. Theor. Appl. Genet. 120: 415-427.
    • (2010) Theor. Appl. Genet. , vol.120 , pp. 415-427
    • Maenhout, S.1    De Baets, B.2    Haesaert, G.3
  • 32
    • 0035045051 scopus 로고    scopus 로고
    • Prediction of total genetic value using genome-wide dense marker maps
    • MEUWISSEN, T. H. E., B. J. HAYES and M. E. GODDARD, 2001 Prediction of total genetic value using genome-wide dense marker maps. Genetics 157: 1819-1829.
    • (2001) Genetics , vol.157 , pp. 1819-1829
    • Meuwissen, T.H.E.1    Hayes, B.J.2    Goddard, M.E.3
  • 33
    • 0036684880 scopus 로고    scopus 로고
    • Algorithms for the computation of T-transitive closures
    • NAESSENS, H., H. DE MEYER and B. DE BAETS, 2002 Algorithms for the computation of T-transitive closures. IEEE Trans. Fuzzy Syst. 10: 541-551.
    • (2002) IEEE Trans. Fuzzy Syst. , vol.10 , pp. 541-551
    • Naessens, H.1    De Meyer, H.2    De Baets, B.3
  • 34
    • 84867997005 scopus 로고    scopus 로고
    • A fast algorithm for the maximum clique problem
    • ÖSTERGÅRD, P. R. J., 2002 A fast algorithm for the maximum clique problem. Discrete Appl. Math. 120: 197-207.
    • (2002) Discrete Appl. Math. , vol.120 , pp. 197-207
    • Östergård, P.R.J.1
  • 35
    • 77956889208 scopus 로고
    • Recovery of interblock information when block sizes are equal
    • PATTERSON, H. D., and R. THOMPSON, 1971 Recovery of interblock information when block sizes are equal. Biometrika 58: 545-554.
    • (1971) Biometrika , vol.58 , pp. 545-554
    • Patterson, H.D.1    Thompson, R.2
  • 36
    • 85029416420 scopus 로고
    • Facility dispersion problems: Heuristics and special cases
    • RAVI, S., D. ROSENKRANTZ and G. TAYI, 1991 Facility dispersion problems: heuristics and special cases. Lecture Notes Comput. Sci. 519: 355-366.
    • (1991) Lecture Notes Comput. Sci. , vol.519 , pp. 355-366
    • Ravi, S.1    Rosenkrantz, D.2    Tayi, G.3
  • 37
    • 34547824749 scopus 로고    scopus 로고
    • Potential causes of linkage disequilibrium in a european maize breeding program investigated with computer simulations
    • STICH, B., A. E. MELCHINGER, H. P. PIEPHO, S. HAMRIT, W. SCHIPPRACK et al., 2007 Potential causes of linkage disequilibrium in a european maize breeding program investigated with computer simulations. Theor. Appl. Genet. 115: 529-536.
    • (2007) Theor. Appl. Genet. , vol.115 , pp. 529-536
    • Stich, B.1    Melchinger, A.E.2    Piepho, H.P.3    Hamrit, S.4    Schipprack, W.5
  • 38
    • 35248814346 scopus 로고    scopus 로고
    • An efficient branch-and-bound algorithm for finding a maximum clique
    • TOMITA, E., and T. SEKI, 2003 An efficient branch-and-bound algorithm for finding a maximum clique. DIMACS Ser. Discrete Math. Theoret. Comput. Sci. 2731: 278-289.
    • (2003) DIMACS Ser. Discrete Math. Theoret. Comput. Sci. , vol.2731 , pp. 278-289
    • Tomita, E.1    Seki, T.2
  • 39
    • 84945708259 scopus 로고
    • A theorem on Boolean matrices
    • WARSHALL, S., 1962 A theorem on Boolean matrices. J. Assoc. Comput. Mach. 9: 11-12.
    • (1962) J. Assoc. Comput. Mach. , vol.9 , pp. 11-12
    • Warshall, S.1
  • 40
    • 31744440502 scopus 로고    scopus 로고
    • A unified mixed-model method for association mapping that accounts for multiple levels of relatedness
    • YU, J., G. PRESSOIR, W. H. BRIGGS, I. VROH BI, M. YAMASAKI et al., 2006 A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat. Genet. 38: 203-208.
    • (2006) Nat. Genet. , vol.38 , pp. 203-208
    • Yu, J.1    Pressoir, G.2    Briggs, W.H.3    Vroh Bi, I.4    Yamasaki, M.5


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