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Integrative Omics: Concept, Methodology, and Application

Editat de Manish Kumar Gupta, Pramod Katara, Sukanta Mondal, Ram Lakhan Singh
en Limba Engleză Paperback – 2 mai 2024
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.


  • Provides a holistic, integrated view of a defining and applying network approach, integrative tools, and methods to solve problems for rationalization of genotype to phenotype relationships
  • Offers an interdisciplinary approach to Databases, data analytics techniques, biological tools, network construction, analysis, modeling, prediction and simulation of biological systems leading to ‘translational research’, i.e., drug discovery, drug target prediction, and precision medicine
  • Covers worldwide methods, concepts, databases, and tools used in the construction of integrated pathways
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Specificații

ISBN-13: 9780443160929
ISBN-10: 0443160929
Pagini: 430
Dimensiuni: 191 x 235 x 25 mm
Greutate: 1.15 kg
Editura: ELSEVIER SCIENCE

Cuprins

  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