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Artykuły w czasopismach na temat "Quantitative genetics"
Mackay, Trudy F. C., Michael Lynch i Bruce Walsh. "Quantitative Genetics". Evolution 53, nr 1 (luty 1999): 307. http://dx.doi.org/10.2307/2640946.
Pełny tekst źródłaGunter, Chris. "Quantitative genetics". Nature 456, nr 7223 (grudzień 2008): 719. http://dx.doi.org/10.1038/456719a.
Pełny tekst źródłaMackay, Trudy F. C. "QUANTITATIVE GENETICS". Evolution 53, nr 1 (luty 1999): 307–9. http://dx.doi.org/10.1111/j.1558-5646.1999.tb05359.x.
Pełny tekst źródłaHill, William G. "Sewall Wright and quantitative genetics". Genome 31, nr 1 (1.01.1989): 190–95. http://dx.doi.org/10.1139/g89-033.
Pełny tekst źródłavan Buijtenen, J. P. "Genomics and quantitative genetics". Canadian Journal of Forest Research 31, nr 4 (1.04.2001): 617–22. http://dx.doi.org/10.1139/x00-171.
Pełny tekst źródłaFRANKHAM, RICHARD. "Quantitative genetics in conservation biology". Genetical Research 74, nr 3 (grudzień 1999): 237–44. http://dx.doi.org/10.1017/s001667239900405x.
Pełny tekst źródłaPlomin, Robert, i Jenae Neiderhiser. "Quantitative Genetics, Molecular Genetics, and Intelligence". Intelligence 15, nr 4 (październik 1991): 369–87. http://dx.doi.org/10.1016/0160-2896(91)90001-t.
Pełny tekst źródłaHansen, Thomas F., i Christophe Pélabon. "Evolvability: A Quantitative-Genetics Perspective". Annual Review of Ecology, Evolution, and Systematics 52, nr 1 (2.11.2021): 153–75. http://dx.doi.org/10.1146/annurev-ecolsys-011121-021241.
Pełny tekst źródłaMacgregor, Stuart, Sara A. Knott, Ian White i Peter M. Visscher. "Quantitative Trait Locus Analysis of Longitudinal Quantitative Trait Data in Complex Pedigrees". Genetics 171, nr 3 (14.07.2005): 1365–76. http://dx.doi.org/10.1534/genetics.105.043828.
Pełny tekst źródłaSlatkin, Montgomery. "Quantitative Genetics of Heterochrony". Evolution 41, nr 4 (lipiec 1987): 799. http://dx.doi.org/10.2307/2408889.
Pełny tekst źródłaRozprawy doktorskie na temat "Quantitative genetics"
Olsson, Charlotta. "Quantitative analysis of disease associated mutations and sequence variants". Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2001. http://publications.uu.se/theses/91-554-5018-0/.
Pełny tekst źródłaSouleman, Dima. "Genetic consequences of colonization of a metal-polluted environment, population genetics and quantitative genetics approaches". Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10006/document.
Pełny tekst źródłaNatural habitats are more and more destructed and fragmented by urban expansion and human activities. The fragmentation of natural and agricultural areas by buildings and new infrastructures affects the size, connectivity and the quality of habitats. The populations of organisms inhabiting these anthropized territories are then more isolated. However, differentiation between populations of the same organism depends on demographic and genetic processes such as genetic drift, gene flow, mutation and natural selection. Only species that have developed special tolerance mechanisms can persist under changed environmental conditions. The introduction of contaminants such as metals in the environment may influence plants and animals evolution by modifying the evolutionary forces and thus generating differences between populations. In this work, attention was focused on the genetic consequences of metallic pollution on two species, the earthworm Lumbricus terrestris and the plant model Arabidopsis halleri. Two different approaches have been used to study the genetic response to metallic contamination: a population genetic approach was performed in L. terrestris and a quantitative genetic approach was carried on in A. halleri. First, it was a question of identifying and validating new microsatellite markers in L. terrestris. These markers were then used to characterize the neutral genetic diversity in worms collected from agricultural and urban sites. Secondly, genetic architecture of Zn tolerance and Zn hyperaccumulation was conducted investigated for the first time using an intraspecific crossing between metallicolous and non-metallicolous individuals of A. halleri. High density of SNP markers was used to proceed to the QTL mapping step
Santure, Anna Wensley, i n/a. "Quantitative genetic models for genomic imprinting". University of Otago. Department of Zoology, 2006. http://adt.otago.ac.nz./public/adt-NZDU20060811.134008.
Pełny tekst źródłaShen, Xia. "Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation". Doctoral thesis, Uppsala universitet, Beräknings- och systembiologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-170091.
Pełny tekst źródłaKeightley, Peter D. "Studies of quantitative genetic variation". Thesis, University of Edinburgh, 1988. http://hdl.handle.net/1842/12340.
Pełny tekst źródłaGunn, Melissa Rose School of Biological Earth & Environmental Science UNSW. "The use of microsatellites as a surrogate for quantitative trait variation in conservation". Awarded by:University of New South Wales. School of Biological, Earth and Environmental Science, 2003. http://handle.unsw.edu.au/1959.4/22457.
Pełny tekst źródłaCerqueira, Pedro Henrique Ramos. "Structural equation models applied to quantitative genetics". Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-05112015-145419/.
Pełny tekst źródłaModelos causais têm sido muitos utilizados em estudos em diferentes áreas de conhecimento, a fim de compreender as associações ou relações causais entre variáveis. Durante as últimas décadas, o uso desses modelos têm crescido muito, especialmente estudos relacionados à sistemas biológicos, uma vez que compreender as relações entre características são essenciais para prever quais são as consequências de intervenções em tais sistemas. Análise do grafo (AG) e os modelos de equações estruturais (MEE) são utilizados como ferramentas para explorar essas relações. Enquanto AG nos permite buscar por estruturas causais, que representam qualitativamente como as variáveis são causalmente conectadas, ajustando o MEE com uma estrutura causal conhecida nos permite inferir a magnitude dos efeitos causais. Os MEE também podem ser vistos como modelos de regressão múltipla em que uma variável resposta pode ser vista como explanatória para uma outra característica. Estudos utilizando MEE em genética quantitativa visam estudar os efeitos genéticos diretos e indiretos associados aos indivíduos por meio de informações realcionadas aos indivíduas, além das característcas observadas, como por exemplo o parentesco entre eles. Neste contexto, é tipicamente adotada a suposição que as características observadas são relacionadas linearmente. No entanto, para alguns cenários, relações não lineares são observadas, o que torna as suposições mencionadas inadequadas. Para superar essa limitação, este trabalho propõe o uso de modelos de equações estruturais de efeitos polinomiais mistos, de segundo grau ou seperior, para modelar relações não lineares. Neste trabalho foram desenvolvidos dois estudos, um de simulação e uma aplicação a dados reais. O primeiro estudo envolveu a simulação de 50 conjuntos de dados, com uma estrutura causal completamente recursiva, envolvendo 3 características, em que foram permitidas relações causais lineares e não lineares entre as mesmas. O segundo estudo envolveu a análise de características relacionadas ao gado leiteiro da raça Holandesa, foram utilizadas relações entre os seguintes fenótipos: dificuldade de parto, duração da gestação e a proporção de morte perionatal. Nós comparamos o modelo misto de múltiplas características com os modelos de equações estruturais polinomiais, com diferentes graus polinomiais, a fim de verificar os benefícios do MEE polinomial de segundo grau ou superior. Para algumas situações a suposição inapropriada de linearidade resulta em previsões pobres das variâncias e covariâncias genéticas diretas, indiretas e totais, seja por superestimar, subestimar, ou mesmo atribuir sinais opostos as covariâncias. Portanto, verificamos que a inclusão de um grau de polinômio aumenta o poder de expressão do MEE.
Mayo, Oliver. "Contributions to quantitative and population genetics : a collection of publications with introduction". Title page, contents and introduction only, 1987. http://web4.library.adelaide.edu.au/theses/09SD/09sdm473.pdf.
Pełny tekst źródłaRandall, Joshua Charles. "Large-scale genetic analysis of quantitative traits". Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:addfb69d-602c-43e3-ab18-6e6d3b269076.
Pełny tekst źródłaWambach, Tina. "Effects of epistatic interaction on detection and parameter analysis of quantitative trait loci". Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=33039.
Pełny tekst źródłaKsiążki na temat "Quantitative genetics"
Xu, Shizhong. Quantitative Genetics. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83940-6.
Pełny tekst źródłaFalconer, D. S. Introductionto quantitative genetics. Wyd. 3. Harlow: Longman Scientific & Technical, 1989.
Znajdź pełny tekst źródłaRoff, Derek A. Evolutionary quantitative genetics. New York: Chapman & Hall, 1997.
Znajdź pełny tekst źródłaRoff, Derek A. Evolutionary Quantitative Genetics. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-4080-9.
Pełny tekst źródłaB, Chapman A., red. General and quantitative genetics. Amsterdam: Elsevier Science Pub. Co., 1985.
Znajdź pełny tekst źródłaHallauer, Arnel R. Quantitative genetics in maize breeding. Wyd. 3. New York: Springer, 2010.
Znajdź pełny tekst źródłaHallauer, Arnel R. Quantitative genetics in maize breeding. Wyd. 3. New York: Springer, 2010.
Znajdź pełny tekst źródłaFalconer, D. S. Introduction to quantitative genetics. Wyd. 3. London: Longman Scientific & Technical, 1989.
Znajdź pełny tekst źródłaFalconer, D. S. Introduction to quantitative genetics. Wyd. 4. Harlow: Prentice Hall, 1996.
Znajdź pełny tekst źródłaFalconer, D. S. Introduction to quantitative genetics. Wyd. 3. Burnt Mill, Harlow, Essex, England: Longman, Scientific & Technical, 1989.
Znajdź pełny tekst źródłaCzęści książek na temat "Quantitative genetics"
Nagylaki, Thomas. "Quantitative Genetics". W Introduction to Theoretical Population Genetics, 279–339. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-76214-7_10.
Pełny tekst źródłaPriyadarshan, P. M. "Quantitative Genetics". W PLANT BREEDING: Classical to Modern, 269–98. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7095-3_14.
Pełny tekst źródłaPrincée, F. P. G. "Quantitative Genetics". W Topics in Biodiversity and Conservation, 219–43. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50032-4_16.
Pełny tekst źródłaChatterjee, Anindo. "Quantitative Genetics". W Genetics Fundamentals Notes, 1029–76. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7041-1_20.
Pełny tekst źródłaKulandhasamy, Maheswari, Sunil Singh i Indrani Mukherjee. "Quantitative Genetics". W Encyclopedia of Animal Cognition and Behavior, 1–3. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-47829-6_168-1.
Pełny tekst źródłaKulandhasamy, Maheswari, Sunil Singh i Indrani Mukherjee. "Quantitative Genetics". W Encyclopedia of Animal Cognition and Behavior, 5837–39. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-55065-7_168.
Pełny tekst źródłaMeredith, William R. "Quantitative Genetics". W Agronomy Monographs, 131–50. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2016. http://dx.doi.org/10.2134/agronmonogr24.c5.
Pełny tekst źródłaCampbell, B. Todd, i Gerald O. Myers. "Quantitative Genetics". W Agronomy Monographs, 187–203. Madison, WI, USA: American Society of Agronomy, Inc., Crop Science Society of America, Inc., and Soil Science Society of America, Inc., 2015. http://dx.doi.org/10.2134/agronmonogr57.2013.0024.
Pełny tekst źródłaLaurentin Táriba, Hernán Eduardo. "Quantitative Genetics". W Agricultural Genetics, 167–78. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37192-9_12.
Pełny tekst źródłaXu, Shizhong. "Resemblance between Relatives". W Quantitative Genetics, 135–46. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83940-6_9.
Pełny tekst źródłaStreszczenia konferencji na temat "Quantitative genetics"
Galas, David, James Kunert-Graf i Nikita Sakhanenko. "Developing an information theory of quantitative genetics". W Entropy 2021: The Scientific Tool of the 21st Century. Basel, Switzerland: MDPI, 2021. http://dx.doi.org/10.3390/entropy2021-09821.
Pełny tekst źródłaSantana, Roberto, Hossein Karshenas, Concha Bielza i Pedro Larrañaga. "Quantitative genetics in multi-objective optimization algorithms". W the 13th annual conference companion. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2001858.2001911.
Pełny tekst źródłaMilkevych, V., E. Karaman, G. Sahana, L. Janss, Z. Cai i M. S. Lund. "351. Quantitative trait simulation using MeSCoT software". W World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_351.
Pełny tekst źródła"Quantitative real-time PCR as a supplementary tool for molecular cytogenetics". W Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 2019. http://dx.doi.org/10.18699/plantgen2019-044.
Pełny tekst źródłaBijma, P., A. D. Hulst i M. C. M. de Jong. "163. A quantitative genetic theory for infectious diseases". W World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_163.
Pełny tekst źródłaDavoodi, P., A. Ehsani, R. Vaez Torshizi i A. A. Masoudi. "596. Chicken quantitative traits follow the omnigenic model". W World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_596.
Pełny tekst źródła"Methods of computer vision to extract the quantitative characteristics of the wheat spike". W Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 2019. http://dx.doi.org/10.18699/plantgen2019-060.
Pełny tekst źródłaTsuruta, S., D. A. L. Lourenco i I. Misztal. "432. Efficient genetic progress for quantitative traits through genomic selection". W World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_432.
Pełny tekst źródła"The association mapping of quantitative resistance loci to net blotch and spot blotch in barley". W Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 2019. http://dx.doi.org/10.18699/plantgen2019-149.
Pełny tekst źródłaTortereau, F., C. Marie-Etancelin, D. Marcon i J. L. Weisbecker. "49. Feed intake can be predicted as quantitative or qualitative traits". W World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_49.
Pełny tekst źródłaRaporty organizacyjne na temat "Quantitative genetics"
Paran, Ilan, i Molly Jahn. Genetics and comparative molecular mapping of biochemical and morphological fruit characters in Capsicum. United States Department of Agriculture, marzec 2005. http://dx.doi.org/10.32747/2005.7586545.bard.
Pełny tekst źródłaZhang, Hongbin B., David J. Bonfil i Shahal Abbo. Genomics Tools for Legume Agronomic Gene Mapping and Cloning, and Genome Analysis: Chickpea as a Model. United States Department of Agriculture, marzec 2003. http://dx.doi.org/10.32747/2003.7586464.bard.
Pełny tekst źródłaBlum, Abraham, Henry T. Nguyen i N. Y. Klueva. The Genetics of Heat Shock Proteins in Wheat in Relation to Heat Tolerance and Yield. United States Department of Agriculture, sierpień 1993. http://dx.doi.org/10.32747/1993.7568105.bard.
Pełny tekst źródłaParan, Ilan, i Molly Jahn. Analysis of Quantitative Traits in Pepper Using Molecular Markers. United States Department of Agriculture, styczeń 2000. http://dx.doi.org/10.32747/2000.7570562.bard.
Pełny tekst źródłaMoore, Gloria A., Gozal Ben-Hayyim, Charles L. Guy i Doron Holland. Mapping Quantitative Trait Loci in the Woody Perennial Plant Genus Citrus. United States Department of Agriculture, maj 1995. http://dx.doi.org/10.32747/1995.7570565.bard.
Pełny tekst źródłaSherman, Amir, Rebecca Grumet, Ron Ophir, Nurit Katzir i Yiqun Weng. Whole genome approach for genetic analysis in cucumber: Fruit size as a test case. United States Department of Agriculture, grudzień 2013. http://dx.doi.org/10.32747/2013.7594399.bard.
Pełny tekst źródłaFeldman, Moshe, Eitan Millet, Calvin O. Qualset i Patrick E. McGuire. Mapping and Tagging by DNA Markers of Wild Emmer Alleles that Improve Quantitative Traits in Common Wheat. United States Department of Agriculture, luty 2001. http://dx.doi.org/10.32747/2001.7573081.bard.
Pełny tekst źródłaOrphan, Victoria, Gene Tyson, Christof Meile, Shawn McGlynn, Hang Yu, Grayson Chadwick, Jeffrey Marlow i in. Systems Level Dissection of Anaerobic Methane Cycling: Quantitative Measurements of Single Cell Ecophysiology, Genetic Mechanisms, and Microbial Interactions. Office of Scientific and Technical Information (OSTI), grudzień 2017. http://dx.doi.org/10.2172/1414771.
Pełny tekst źródłaSanta Sepúlveda, Juan David, Jhon Berdugo Cely, Mauricio Soto Suárez, Teresa Mosquera i Carlos Galeano. A genetic linkage map of tetraploid potato (Solanum tuberosum L.) for Phytophthora infestans and Tecia solanivora quantitative resistance. Corporación Colombiana de Investigación Agropecuaria - AGROSAVIA, 2016. http://dx.doi.org/10.21930/agrosavia.poster.2016.28.
Pełny tekst źródłaWeller, Joel I., Harris A. Lewin i Micha Ron. Determination of Allele Frequencies for Quantitative Trait Loci in Commercial Animal Populations. United States Department of Agriculture, luty 2005. http://dx.doi.org/10.32747/2005.7586473.bard.
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