Integrative Omics: Concept, Methodology, and Application
Editat de Manish Kumar Gupta, Pramod Katara, Sukanta Mondal, Ram Lakhan Singhen Limba Engleză Paperback – 2 mai 2024
- 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
ISBN-10: 0443160929
Pagini: 430
Dimensiuni: 191 x 235 x 25 mm
Greutate: 1.15 kg
Editura: ELSEVIER SCIENCE
Cuprins
- 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