
Omics Approaches and Technologies in COVID-19
- 1st Edition - December 1, 2022
- Imprint: Academic Press
- Editors: Debmalya Barh, Vasco Ariston De Car Azevedo
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 1 7 9 4 - 0
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 8 6 2 1 - 2
The COVID-19 pandemic has affected the entire world in an unprecedented way since 2019. However, novel and innovative applications of various omics, computational, and smart te… Read more

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Request a sales quoteThe COVID-19 pandemic has affected the entire world in an unprecedented way since 2019. However, novel and innovative applications of various omics, computational, and smart technologies have helped manage the pandemic of the 21st century in a very effective manner. Omics approaches and technologies in COVID-19 presents up-to-date knowledge on omics, genetic engineering, mathematical and computational approaches, and advanced technologies in the diagnosis, prevention, monitoring, and management of COVID-19.
This book contains 26 chapters written by academic and industry experts from more than 15 countries. Split into three sections (Omics; Artificial Intelligence and Bioinformatics; and Smart and Emerging Technologies), it brings an overview of novel technologies under omics such as, genomic, metagenomic, pangenomic, metabolomics and proteomics in COVID-19. In addition, it discusses hostpathogen interactions and interactomics, management options, application of genetic engineering, mathematical modeling and
simulations, systems biology, and bioinformatics approaches in COVID-19 drug discovery and vaccine development.
This is a valuable resource for students, biotechnologists, bioinformaticians, virologists, clinicians, and pharmaceutical, biomedical, and healthcare industry people who want to understand the promising omics and other technologies used in combating COVID-19 from various aspects.
- Provides novel technologies for rapid diagnostics, drug discovery, vaccine development, monitoring, prediction of future waves, etc.
- Describes various omics applications including genomics, metagenomics, epigenomics, nutrigenomics, transcriptomics,miRNAomics, proteomics, metabolomics, phenomics, multiomics, etc., in COVID-19
- Presents applications of genetic engineering, CRISPR, artificial intelligence, mathematical and in silico modeling, systems biology,and other computational approaches in COVID-19
- Discusses emerging, digital, and smart technologies for the monitoring and management of COVID-19
- Cover
- Title page
- Table of Contents
- Copyright
- Dedication
- Contributors
- About the editors
- Preface
- Section A: Omics
- Chapter 1: Omics approaches in COVID-19: An overview
- Abstract
- 1: Introduction
- 2: Genomics, meta-genomics, and pan-genomics approaches
- 3: Genotype-phenotype correlations in COVID-19
- 4: Proteomics in COVID-19
- 5: Host-pathogen protein—Protein interactions and interactomics
- 6: Currently available COVID-19 management options
- 7: Transcriptomic approaches in COVID-19: From infection to vaccines
- 8: miRNAomics in COVID-19
- 9: Epigenetic implementations in COVID-19
- 10: Nutrigenomics and nutrition aspects in COVID-19
- 11: COVID-19 and phenomics
- 12: Metabolomics in COVID-19
- 13: Applications of genetic engineering in COVID-19
- 14: CRISPR-based assays for rapid detection of SARS-CoV2
- 15: Approaches to understand the emergence and dynamics of COVID-19 and future pandemics
- 16: Artificial intelligence (AI) in COVID-19
- 17: Applications of mathematical modeling and simulation in COVID-19
- 18: In silico disease modeling for COVID-19
- 19: System biology applications in COVID-19
- 20: Computational approaches in COVID-19 drug discovery
- 21: Computational approaches in COVID-19 vaccine development
- 22: Applications of multiomics data in COVID-19
- 23: Publicly available resources in COVID-19 research and their applications
- 24: Emerging technologies for COVID-19 diagnosis, prevention, and management
- 25: Applications of digital and smart technologies to control SARS-CoV2 transmission, rapid diagnosis, and monitoring
- 26: Technologies for prediction of a patient’s health condition and outcomes from COVID-19
- 27: Conclusion and overall implications
- References
- Chapter 2: Genomics, metagenomics, and pan-genomics approaches in COVID-19
- Abstract
- 1: Introduction
- 2: Metagenomic analysis
- 3: Covid-19 pangenome dynamics
- 4: Application and advancement of pan genome-derived data in therapeutics
- 5: Implementations of SARS-CoV-2 genomics, metagenomics, and pan-genomics approaches
- 6: Conclusion and future perspectives
- References
- Chapter 3: Genotype and phenotype correlations in COVID-19
- Abstract
- 1: Introduction
- 2: Structure and lifecycle of coronavirus
- 3: COVID-19 susceptibility genes identified by GWASs and implications of these genes in developing COVID-19 disease subphenotypes
- 4: The cellular pathway of these SNPs/genes leading to COVID-19 subphenotypes
- 5: Genetic variations associated with susceptibility and severity to COVID-19
- 6: Epigenetic mechanisms of SARS-CoV-2 infection and associated comorbidities
- 7: Genetic variations and impact on diagnosis and treatment
- 8: Implementations of genotype-phenotype correlations in COVID-19
- 9: Other implementations
- References
- Chapter 4: Proteomic understanding of SARS-CoV-2 infection and COVID-19: Biological, diagnostic, and therapeutic perspectives
- Abstract
- 1: Introduction
- 2: Proteome of the SARS-CoV-2 virus
- 3: Host-pathogen protein-protein interactions in COVID-19
- 4: Proteomics in COVID-19 patients
- 5: Posttranslational modifications in COVID-19
- 6: Proteomics tools and applications for COVID-19
- 7: Implementations of SARS-CoV-2 and COVID-19 proteomics
- 8: Critical analyses of the present achievements and future perspectives
- References
- Chapter 5: Metabolites and metabolomics in COVID-19
- Abstract
- 1: Introduction
- 2: Metabolites and metabolomics in viral infection
- 3: Metabolomics in SARS-CoV-2
- 4: Implementation of metabolites/metabolomics in COVID-19
- 5: Conclusions and future perspectives
- References
- Chapter 6: Host-pathogen protein-protein interactions and interactomics in COVID-19
- Abstract
- 1: Introduction
- 2: Comparative interactomics: How the SARS-CoV-2 PPI differs from SARS-CoV-1 and other viruses
- 3: PPI-based pathway interactions in COVID-19
- 4: Interactome datasets and tools available to the community on COVID-19
- 5: Implementations of SARS-CoV-2 and human PPI/translational interactomics
- 6: The search for druggable targets through ACE2 protein-protein interaction networks (PPINs)
- 7: Bioinformatics-based HPI and their implementations
- 8: Comparative coronavirus interactomics and host targets
- 9: Drug repurposing
- 10: Understanding the mechanism of multiorgan injuries and their sequels
- 11: Critical analyses of the present achievements
- 12: Conclusion and future perspectives
- References
- Chapter 7: Currently available COVID-19 management options
- Abstract
- 1: Introduction
- 2: General treatment strategies
- 3: Specific treatments
- 4: Antiviral therapies
- 5: Anti-SARS-CoV-2 neutralizing antibody products
- 6: Immunomodulatory agents
- 7: Ventilation management and oxygenation in COVID-19
- 8: Management of critical cases
- 9: Supplementation
- 10: Vitamin D
- 11: Vitamin C
- 12: Zinc
- 13: Magnesium
- 14: Vitamin B12
- 15: Alpha-lipoic acid
- 16: Management of postinfection complications
- 17: Conclusions and future perspectives
- References
- Chapter 8: Transcriptomic approaches in COVID-19: From infection to vaccines
- Abstract
- 1: Introduction
- 2: The structural basis of SARS-CoV-2 transcriptome
- 3: Transcriptional host responses to SARS-CoV-2 infection
- 4: Implementations of transcriptomics in COVID-19
- 5: Single-cell transcriptomics in COVID-19
- 6: Conclusions and perspectives
- References
- Chapter 9: miRNAomics in COVID-19
- Abstract
- 1: Introduction
- 2: miRNA expression profile in COVID-19
- 3: Interactions of SARS-CoV-2 miRNA/small RNAs and host miRNA
- 4: SARS-CoV-2 encoded miRNAs/small RNAs in SARS-CoV-2 infection and COVID-19 pathology
- 5: Host miRNA/small noncoding RNAs and COVID-19 pathology/severity/host response
- 6: miRNA perspective of comorbid conditions and long-haul COVID
- 7: Implementations of miRNAs in
- 8: List of miRNA therapeutics in clinical trials
- 9: Conclusion and future perspectives
- References
- Chapter 10: Epigenetic features, methods, and implementations associated with COVID-19
- Abstract
- 1: Introduction
- 2: Epigenetic landscape alteration and epigenetic mechanisms in respiratory viral infections
- 3: Cutting-edge epigenetics and epigenomics technology applied in COVID-19
- 4: Epigenetic landscape and mechanism in SARS-CoV-2 entry and infection
- 5: Interactions between human epigenetic factors and SARS-CoV-2 proteins
- 6: Epigenetic biomarkers for COVID-19 risk and severity
- 7: Epitranscriptome profiling, technology, outcomes, and implementations in COVID-19
- 8: Epitherapy and epidrug repurposing in COVID-19 clinical trials
- 9: Implementations of SARS-CoV-2 epigenetics/epigenomics
- 10: Conclusion and future perspectives
- References
- Chapter 11: Nutrigenetics and nutrition aspects in COVID-19
- Abstract
- 1: Introduction of nutrigenetics
- 2: Gene-diet interaction and precision nutrition in COVID-19
- 3: Various diet components and their cellular and molecular effects on COVID-19
- 4: Recent updates of nutrigenomic studies in COVID-19
- 5: Link of COVID-19 to low mortality of Asians compared to Americans and Europeans
- 6: Conclusions and future perspectives
- References
- Chapter 12: COVID-19 phenomics
- Abstract
- 1: Introduction to phenomics in the context of viral disease
- 2: Phenomic approaches to COVID-19
- 3: Applications of phenomics to COVID-19
- 4: Concluding remarks
- References
- Chapter 13: Applications of genetic engineering in COVID-19
- Abstract
- Conflict of interest
- 1: Introduction
- 2: SARS-CoV-2 protein production during the lifecycle emphasizes important posttranslation modifications
- 3: Application of subunit spike protein production
- 4: Production of recombinant virus and virus-like particles
- 5: Genetically engineered models
- 6: Synthetic biology of SARS-CoV-2
- 7: Concluding remarks
- References
- Chapter 14: CRISPR-based assays for rapid detection of SARS-CoV-2
- Abstract
- 1: Introduction
- 2: SHERLOCK—CRISPR-Cas13a enzyme-based COVID-19 detection assay
- 3: DETECTR—CRISPR-Cas12a enzyme-based detection assay
- 4: AIOD-CRISPR—All-in-one dual CRISPR-Cas12a assay
- 5: CRISPRENHANCE—Enhanced analysis of nucleic acids with crRNA extensions assay
- 6: CASdetec—CRISPR-Cas12b-mediated DNA detection assay
- 7: FELUDA—CRISPR-Cas9 enzyme-based detection assay
- 8: Conclusion
- References
- Section B: Artificial intelligence and bioinformatics
- Chapter 15: Emergence and dynamics of COVID-19 and future pandemics
- Abstract
- 1: Differentiating the disease and infection
- 2: The weight of preconceived ideas
- 3: The example of COVID-19
- 4: The “medical approach”
- 5: The “environmental approach”
- 6: The “laboratory leak narratives”
- 7: The “Circulation” model and the evolution of viruses in the human population
- 8: The genetic accident
- 9: The societal accident
- 10: An intermediate summary
- 11: What can be performed to prevent the occurrence of further pandemics?
- 12: Conclusion: The solution is in the societal management
- References
- Chapter 16: Artificial intelligence in COVID-19
- Abstract
- 1: Introduction
- 2: Background
- 3: AI implementations for COVID-19
- 4: Conclusion
- References
- Chapter 17: Applications of mathematical modeling and simulation in COVID-19
- Abstract
- 1: The basic principles and applications of mathematical modeling and simulation in pandemics
- 2: Data sets and various mathematical models applied to COVID-19
- 3: Implementations of modeling and simulation
- 4: Limitations and potential challenges of modeling and simulation in COVID-19
- 5: Conclusions and future perspectives
- References
- Chapter 18: In silico disease modeling for COVID-19
- Abstract
- 1: Introduction: COVID-19 models
- 2: In silico modeling of infectious disease: Types of models and biological implications
- 3: In silico modeling of SARS-COV-2 dynamics within the host
- 4: Implementations of in silico modeling of COVID-19
- 5: Conclusions
- References
- Chapter 19: Systems biology in COVID-19
- Abstract
- 1: Introduction
- 2: Strategies, tools, DBs, and other publicly available resources for COVID-19 systems biology and phenomics
- 3: Implementations of systems biology in COVID-19 in basic and translational research
- 4: Systems pharmacology approaches in identifying the targetome, therapeutics, and prophylactic agents for COVID-19
- 5: Other implementations: Big data, phenomics, and radiomics
- 6: Critical analyses of the present achievements
- 7: Conclusion and future perspectives
- References
- Chapter 20: Computational approaches for drug discovery against COVID-19
- Abstract
- 1: Introduction
- 2: Computational approaches to identify drug targets in SARS-CoV-2 and humans
- 3: In silico approaches to identify candidate drugs
- 4: Potential anti-COVID drugs based on computational approaches
- 5: Identification of prophylaxis and COVID-19 management agents (such as NO etc.) using in silico approaches
- 6: In silico disease (COVID-19) modeling for testing the efficacy of candidate therapeutics
- 7: Critical analyses of the present achievements
- 8: Conclusion and future perspectives
- References
- Chapter 21: Computational approaches in COVID-19 vaccine development
- Abstract
- 1: Why is the vaccine the best way to fight COVID-19?
- 2: Steps in the development of conventional vaccines and their difficulties and disadvantages
- 3: How the computational approaches speed up the vaccine design and development process
- 4: The concept of computational immunology and the available resources
- 5: Computational immune proteomics approach in COVID vaccine design and outcomes
- 6: Reverse vaccinology-based approach in COVID vaccine design and outcomes
- 7: Identified epitope and multiepitope-based peptide vaccines against COVID-19
- 8: Computer-aided mRNA vaccine design against COVID-19
- 9: Computer-aided DNA vaccine design against COVID-19
- 10: Artificial intelligence and systems biology approaches in COVID-19 vaccine development
- 11: Computational approaches for rapid design, development, and testing the efficacy of COVID-19 vaccines
- 12: Computational approaches applied in various vaccine development platforms for COVID-19
- 13: The currently available vaccines and the computational approaches behind these vaccines
- 14: Computational approaches to validate the efficacy of the developed vaccines against COVID-19
- 15: Tools and applications used in tracking the COVID-19 vaccination regime
- 16: Publicly available resources for COVID-19 vaccine discovery
- 17: Critical analyses of the present achievements
- 18: Conclusion and future perspectives
- References
- Chapter 22: Applications of multiomics data in COVID-19
- Abstract
- 1: Omics and multiomics approaches: Data, data integration, and analysis
- 2: Multiomics approaches to decode SARS-CoV-2 infection biology
- 3: Multiomics approaches to understand how nCoV hijacks the host cell machinery
- 4: Multiomics approaches to understand the comorbid conditions and COVID-19 interactions
- 5: Multiomics approaches for personalized and targeted therapy and care to COVID-19 patients
- 6: Early diagnosis and multiomics-based screening of biomarkers for the COVID-susceptible population
- 7: Developing a preventive strategy and multiomics approach toward the formulation of prophylaxis agents/strategies
- 8: Developing therapeutics and management for mild and severe COVID-19 cases
- 9: Multiomics approaches toward multiple organ injury and response because of COVID-19
- 10: Multiomics-based prediction of long-term health consequences and their treatment options in recovered patients
- 11: Conclusion
- References
- Chapter 23: Publicly available resources in COVID-19 research and their applications
- Abstract
- 1: Introduction
- 2: Literature resources
- 3: Epidemiology resources
- 4: SARS-CoV-2-specific genomic databases and tools for analysis
- 5: SARS-CoV-2-specific proteomic databases and tools for analysis
- 6: SARS-CoV-2-specific epigenetic databases and tools for analysis
- 7: SARS-CoV-2-specific transcriptomic databases and tools for analysis
- 8: In vivo and clinical trial databases for COVID-19 drugs
- 9: Bioinformatics tools and databases for SARS-CoV-2 drug designing and vaccine developments
- 10: Toxicogenomic databases and tools for SARS-CoV-2 research
- 11: Resources and tools for clinicians
- 12: Mobile apps for tracking the pandemic
- 13: Conclusion and future perspectives
- References
- Section C: Smart and emerging technologies
- Chapter 24: Emerging technologies for COVID-19, diagnosis, prevention, and management
- Abstract
- 1: Introduction
- 2: Emerging technologies for diagnosing SARS-CoV-2
- 3: Emerging technologies for studying the COVID-19 epidemiology
- 4: Technologies for prevention and control the SARS-CoV-2 transmission
- 5: Emerging technologies for therapeutic and vaccine development
- 6: Conclusion and future perspectives
- References
- Chapter 25: Applications of digital and smart technologies to control SARS-CoV-2 transmission, rapid diagnosis, and monitoring
- Abstract
- 1: Introduction
- 2: Digital and smart technologies used in the COVID pandemic
- 3: Implementation of digital and smart technologies in COVID-19
- 4: Technologies for Integration of various sectors (clinical, environmental, public and private, hospitals, health care centers to the individual public, etc.)
- 5: Emerging smart and digital tech for research purposes
- 6: Comparison of smart and digital techs implemented for pandemic management between first and third world economic countries
- 7: Advantages, disadvantages, and risks of the currently used smart and digital technologies in the COVID pandemic
- 8: Ethical perspective and steps to ensure data safety
- 9: Conclusion and future perspectives
- References
- Chapter 26: Application of big data analytics in the COVID-19 pandemic: Selected problems
- Abstract
- Acknowledgments
- 1: Introduction
- 2: Challenges in COVID-19 and big data
- 3: Recommendations
- 4: Conclusion
- References
- Index
- Edition: 1
- Published: December 1, 2022
- Imprint: Academic Press
- No. of pages: 462
- Language: English
- Paperback ISBN: 9780323917940
- eBook ISBN: 9780323986212
DB
Debmalya Barh
VA