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02238nam a22003015i 4500 |
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978-1-4939-2155-3 |
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141117s2015 xxu| s |||| 0|eng d |
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|a 9781493921553
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|a 10.1007/978-1-4939-2155-3
|2 doi
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|a Sistema de Bibliotecas del Tecnológico de Costa Rica
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|a Epistasis
|b Methods and Protocols /
|c edited by Jason H. Moore, Scott M. Williams.
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|a 1st ed. 2015.
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|a New York, NY :
|b Springer New York :
|b Imprint: Humana,
|c 2015.
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|a X, 350 p. 61 illus., 17 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Methods in Molecular Biology,
|v 1253
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|a Long Term Selection Experiments: Epistasis and The Response To Selection -- Finding the Epistasis Needles in the Genome-Wide Haystack -- Biological Knowledge-Driven Analysis of Epistasis in Human GWAS with Application to Lipid Traits -- Epistasis for Quantitative Traits in Drosophila -- Epistasis In The Risk Of Human Neuropsychiatric Disease -- On the Partitioning of Genetic Variance with Epistasis -- Measuring Gene Interactions -- Two Rules for the Detection and Quantification of Epistasis and other Interaction Effects -- Direct Approach to Modeling Epistasis -- Capacitating Epistasis - Detection and Role in the Genetic Architecture of Complex Traits -- Compositional Epistasis: An Epidemiologic Perspective -- Identification Of Genome-Wide SNP-SNP and SNP-Clinical Boolean Interactions In Age-Related Macular Degeneration -- Epistasis Analysis Using Information Theory -- Genome-Wide Epistasis and Pleiotropy Characterized by the Bipartite Human -- Network Theory for Data-Driven Epistasis Networks -- Epistasis Analysis Using Multifactor Dimensionality Reduction -- Epistasis Analysis Using ReliefF -- Epistasis Analysis Using Artificial Intelligence.
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|a Human genetics.
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|a Human Genetics.
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|a Moore, Jason H.
|e editor.
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|a Williams, Scott M.
|e editor.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|u https://doi.org/10.1007/978-1-4939-2155-3
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