Integrative Omics

Concept, Methodology, and Application
Herausgeber: Gupta, Manish Kumar; Singh, Ram Lakhan; Mondal, Sukanta; Katara, Pramod

• Broschiertes Buch

Produktbeschreibung

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.

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Produktdetails

• Verlag: Elsevier Science Publishing Co Inc
• Seitenzahl: 430
• Erscheinungstermin: 3. Mai 2024
• Englisch
• Abmessung: 235mm x 191mm
• Gewicht: 1148g
• ISBN-13: 9780443160929
• ISBN-10: 0443160929
• Artikelnr.: 68355053

Inhaltsangabe

1. From Omics to Multi-integrative Omics Approach
2. Types Of Omics Data: Genomics, Metagenomics, Epigenomics,
Transcriptomics, Proteomics, Metabolomics and Phenomics
3. Biological Omics databases and Tools
4. Systematic Benchmarking of Omics Computational Tools
5. Pharmacogenomics, Nutrigenomics, and Microbial Omics
6. Proteomics: Present and Future Prospectives
7. Foodomics: Integrated Omics for the Food and Nutrition Science
8. Vaccinomics
9. Integrative Omics Approach for Identification of Genes Associated
with Disease
10. Integrative Omics Approaches for Identification of Biomarkers
11. Omics Approach for Personalized and Diagnostics Medicine
12. Role of Bioinformatics in Genome Analysis
13. Data Management in Cross Omics
14. Omics and Clinical Data Integration and Data Warehousing
15. Integrative Omics Data Mining: Challenges and Opportunities
16. Data Science and Analytics, Modeling, Simulation, and Issues of Omics
Data Set
17. Emerging Trends in Translational Omics
18. Omics Technology for Crop Improvement
19. Ecology and Environmental Omics
20. Current Trends and Approaches in Clinical Metagenomics
21. Bio-molecular Networks
22. Machine Learning Fundamentals to Explore Complex OMICS Data
23. Omics Technology Policy and Society Research