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Full Description
Integrative Omics: Concept, Methodology and Application provides a holistic and integrated view of defining and applying network approaches, integrative tools, and methods to solve problems for the rationalization of genotype to phenotype relationships. The reference provides systemic 'step-by-step' coverage that begins with basic concepts from Omic to Multi Integrative Omics approaches followed by applications and emerging and future trends. All areas of Omics are covered, including biological databases, sequence alignment, pharmacogenomics, nutrigenomics and microbial omics, integrated omics for Food Science and Identification of genes associated with disease, clinical data integration and data warehousing, translational omics, technology policy, and society research. This book covers recent concepts, methodologies, advancements in technologies and is also well-suited for researchers from both academic and industry background, undergraduate and graduate students who are mainly working in the area of computational systems biology, integrative omics and translational science.
Contents
From Omics to Multi-integrative Omics Approach
Types Of Omics Data: Genomics, Metagenomics, Epigenomics, Transcriptomics, Proteomics, Metabolomics and Phenomics
Biological Omics databases and Tools
Systematic Benchmarking of Omics Computational Tools
Pharmacogenomics, Nutrigenomics, and Microbial Omics
Proteomics: Present and Future Prospectives
Foodomics: Integrated Omics for the Food and Nutrition Science
Vaccinomics
Integrative Omics Approach for Identification of Genes Associated with Disease
Integrative Omics Approaches for Identification of Biomarkers
Omics Approach for Personalized and Diagnostics Medicine
Role of Bioinformatics in Genome Analysis
Data Management in Cross Omics
Omics and Clinical Data Integration and Data Warehousing
Integrative Omics Data Mining: Challenges and Opportunities
Data Science and Analytics, Modeling, Simulation, and Issues of Omics Data Set
Emerging Trends in Translational Omics
Omics Technology for Crop Improvement
Ecology and Environmental Omics
Current Trends and Approaches in Clinical Metagenomics
Bio-molecular Networks
Machine Learning Fundamentals to Explore Complex OMICS Data
Omics Technology Policy and Society Research
