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03148nam a22003375i 4500 |
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000283029 |
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20210510095708.0 |
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cr nn 008mamaa |
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130612s2013 xxu| s |||| 0|eng d |
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|a 9781627034470
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| 024 |
7 |
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|a 10.1007/978-1-62703-447-0
|2 doi
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| 040 |
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|a Sistema de Bibliotecas del Tecnológico de Costa Rica
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| 245 |
1 |
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|a Genome-Wide Association Studies and Genomic Prediction /
|c edited by Cedric Gondro, Julius van der Werf, Ben Hayes.
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| 250 |
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|a 1st ed. 2013.
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| 260 |
# |
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|a Totowa, NJ :
|b Humana Press :
|b Imprint: Humana,
|c 2013.
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| 300 |
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|a XI, 566 p. 67 illus., 31 illus. in color. :
|b online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
1 |
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|a Methods in Molecular Biology,
|v 1019
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| 505 |
0 |
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|a R for Genome-Wide Association Studies -- Descriptive Statistics of Data: Understanding the Data Set and Phenotypes of Interest -- Designing a Genome-Wide Association Studies (GWAS): Power, Sample Size, and Data Structure -- Managing Large SNP Datasets with SNPpy -- Quality Control for Genome-Wide Association Studies -- Overview of Statistical Methods for Genome-Wide Association Studies (GWAS) -- Statistical Analysis of Genomic Data -- Using PLINK for Genome-Wide Association Studies (GWAS) and Data Analysis -- Genome-Wide Complex Trait Analysis (GCTA): Methods, Data Analyses, and Interpretations -- Bayesian Methods Applied to Genome-Wide Association Studies (GWAS) -- Implementing a QTL Detection Study (GWAS) Using Genomic Prediction Methodology -- Genome-Enabled Prediction Using the BLR (Bayesian Linear Regression) R-Package -- Genomic Best Linear Unbiased Prediction (gBLUP) for the Estimation of Genomic Breeding Values -- Detecting Regions of Homozygosity to Map the Cause of Recessively Inherited Disease -- Use of Ancestral Haplotypes in Genome-Wide Association Studies -- Genotype Phasing in Populations of Closely Related Individuals -- Genotype Imputation to Increase Sample Size in Pedigreed Populations -- Validation of Genome-Wide Association Studies (GWAS) Results -- Detection of Signatures of Selection Using FST -- Association Weight Matrix: A Network-Based Approach Towards Functional Genome-Wide Association Studies -- Mixed Effects Structural Equation Models and Phenotypic Causal Networks -- Epistasis, Complexity, and Multifactor Dimensionality Reduction -- Applications of Multifactor Dimensionality Reduction to Genome-Wide Data Using the R Package 'MDR' -- Higher Order Interactions: Detection of Epistasis Using Machine Learning and Evolutionary Computation -- Incorporating Prior Knowledge to Increase the Power of Genome-Wide Association Studies -- Genomic Selection in Animal Breeding Programs.
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| 650 |
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0 |
|a Bioinformatics.
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| 650 |
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0 |
|a Human genetics.
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| 650 |
1 |
4 |
|a Bioinformatics.
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| 650 |
2 |
4 |
|a Human Genetics.
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| 700 |
1 |
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|a Gondro, Cedric.
|e editor.
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| 700 |
1 |
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|a van der Werf, Julius.
|e editor.
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| 700 |
1 |
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|a Hayes, Ben.
|e editor.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 900 |
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|a Libro descargado a ALEPH en bloque (proveniente de proveedor)
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