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|Additional Physical Format:||Print version:
Kadarmideen, Haja N.
Systems Biology in Animal Production and Health, Vol. 1
Cham : Springer International Publishing,c2016
|Material Type:||Document, Internet resource|
|Document Type:||Internet Resource, Computer File|
|All Authors / Contributors:||
Haja N Kadarmideen
|Notes:||Description based upon print version of record.
8 Statistical Techniques for Experimental Data Analysis
|Description:||1 online resource (161 p.)|
|Contents:||Foreword; Preface; Contents; Detection of Regulator Genes and eQTLs in Gene Networks; 1 Introduction; 2 Genetics of Gene Expression; 3 Coexpression Networks and Modules; 3.1 Coexpression Gene Networks; 3.2 Clustering and Coexpression Module Detection; 3.2.1 Modularity Maximization; 4 Causal Gene Networks; 4.1 Using Genotype Data to Prioritize Edge Directions in Coexpression Networks; 4.2 Using Bayesian Networks to Identify Causal Regulatory Mechanisms; 4.3 Using Module Networks to Identify Causal Regulatory Mechanisms; 4.4 Illustrative Example 5 In Silico Validation of Predicted Gene Regulation Networks6 Future Perspective: Integration of Multi-Omics Data; Conclusions; References; Applications of Systems Genetics and Biology for Obesity Using Pig Models; 1 The Pig as a Model for Human Obesity; 2 The Complexity of Human Obesity in a Nutshell; 3 Single Gene Studies in Obesity: What Do We Know So Far?; 4 Human Obesity Genes Present in Pigs; 5 Studying the Genetics of Fatness Traits in Pigs: Input from the Industry; 6 Porcine Models for Human Obesity; 7 Systems Genetics Analyses of Obesity Using a Porcine Model 8 Future PerspectivesReferences; Merging Metabolomics, Genetics, and Genomics in Livestock to Dissect Complex Production Traits; 1 Introduction; 2 Metabolites and Metabolomics; 2.1 Analytical Platforms in Metabolomics; 2.2 Data Analysis in Metabolomics; 3 Metabolomics for the Dissection of Complex Traits in Livestock; 3.1 Heritability of Metabotypes; 3.2 Metabotypes as Predictors of Economic Relevant Traits; 3.3 Metabolomics and Genomics; 3.4 A Simplified Systems Genetic Approach in Livestock; Conclusions; References; RNA Sequencing Applied to Livestock Production; 1 Introduction 2 Steps in RNA-seq Data Analysis and the Tools Available2.1 Quality Control and Preprocessing; 2.2 Alignment of Reads to a Reference Genome or Transcriptome; 2.3 Assembly; 2.4 Alternative Splicing; 2.5 Functional Analysis; 3 Applications in Livestock; 4 Appendix-A Simple Example of RNA-seq Gene Expression Data Analysis Using R and Other Software; References; Applications of Graphical Models in Quantitative Genetics and Genomics; 1 Introduction; 2 Bayesian Networks; 3 Examples of Applications of Bayesian Networks; 3.1 Parsimonious Modeling of Multidimensional Covariance Structures 3.2 Prediction of Complex Phenotypic Traits3.3 Causal Inference; 3.4 Additional Applications; 4 Concluding Remarks; References; Advanced Computational Methods, NGS Tools, and Software for Mammalian Systems Biology; 1 Introduction; 2 Multiscale-Multi-omics Data; 3 Known and Commonly Used Biological Data Representations; 4 Evidence-Based Reasoning; 5 Integration Through Reduction; 6 iOMICS for Genomics Data Analysis; 6.1 Genome; 6.2 Epigenome; 6.3 Transcriptome; 6.4 Small RNA; 6.5 Phenotype Modeling; 7 Reference Biological Databases|
|Responsibility:||Haja N. Kadarmideen, editor.|