Integrative Omics
Concept, Methodology, and Application
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Product details:
- Publisher Elsevier Science
- Date of Publication 3 May 2024
- ISBN 9780443160929
- Binding Paperback
- No. of pages430 pages
- Size 235x191 mm
- Weight 1200 g
- Language English 559
Categories
Long 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.
MoreTable of 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
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