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Systems Biology in Animal Production and Health, Vol. 1

Author: Haja N Kadarmideen
Publisher: Cham : Springer, 2016.
Edition/Format:   eBook : Document : English
Database:WorldCat
Summary:
This two-volume work provides an overview on various state of the art experimental and statistical methods, modeling approaches and software tools that are available to generate, integrate and analyze multi-omics datasets in order to detect biomarkers, genetic markers and potential causal genes for improved animal production and health. The book will contain online resources where additional data and programs can be  Read more...
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Genre/Form: Electronic books
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
ISBN: 9783319433356 3319433350
OCLC Number: 961449267
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.
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Abstract:

This two-volume work provides an overview on various state of the art experimental and statistical methods, modeling approaches and software tools that are available to generate, integrate and analyze multi-omics datasets in order to detect biomarkers, genetic markers and potential causal genes for improved animal production and health. The book will contain online resources where additional data and programs can be accessed. Some chapters also come with computer programming codes and example datasets to provide readers hands-on (computer) exercises. This first volume presents the basic principles and concepts of systems biology with theoretical foundations including genetic, co-expression and metabolic networks. It will introduce to multi omics components of systems biology from genomics, through transcriptomics, proteomics to metabolomics. In addition it will highlight statistical methods and (bioinformatic) tools available to model and analyse these data sets along with phenotypes in animal production and health. This book is suitable for both students and teachers in animal sciences and veterinary medicine as well as to researchers in this discipline.

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