Bioinformatics

Methods and Applications

1st Edition - October 21, 2021
Imprint: Academic Press
Editors: Dev Bukhsh Singh, Rajesh Kumar Pathak
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 8 9 7 7 5 - 4
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 0 0 0 5 - 8
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 0 3 7 9 - 0

Bioinformatics: Methods and Applications provides a thorough and detailed description of principles, methods, and applications of bioinformatics in different areas of life scienc… Read more

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Bioinformatics: Methods and Applications provides a thorough and detailed description of principles, methods, and applications of bioinformatics in different areas of life sciences. It presents a compendium of many important topics of current advanced research and basic principles/approaches easily applicable to diverse research settings. The content encompasses topics such as biological databases, sequence analysis, genome assembly, RNA sequence data analysis, drug design, and structural and functional analysis of proteins. In addition, it discusses computational approaches for vaccine design, systems biology and big data analysis, and machine learning in bioinformatics.It is a valuable source for bioinformaticians, computer biologists, and members of biomedical field who needs to learn bioinformatics approaches to apply to their research and lab activities.

Cover image
Title page
Table of Contents
Copyright
List of contributors
Preface
Chapter 1. Introduction to basics of bioinformatics
Abstract
1.1 Introduction
1.2 Historical background of bioinformatics
1.3 Aim of bioinformatics
1.4 The recent development in the field of bioinformatics
1.5 Challenges in bioinformatics
1.6 Application of bioinformatics
1.7 Future perspective
1.8 Conclusion
Conflict of interest
References
Chapter 2. Biological databases and their application
Abstract
2.1 Introduction
2.2 Sequence databases
2.3 Composite database
2.4 Secondary database
2.5 Structural databases
2.6 Specialized database
2.7 Database searching and annotation
2.8 Conclusions
Conflict of interest
References
Chapter 3. Biological sequence analysis
Abstract
3.1 Introduction
3.2 Sequence alignments: determining similarity and deducing homology
3.3 Scoring matrices: construction and proper selection
3.4 Basic Local Alignment Search Tool
3.5 Multiple sequence alignment (MSA)
3.6 Phylogenetic analysis
3.7 Application of sequence alignment
3.8 Conclusion
Conflict of interest
References
Chapter 4. Genome assembly and annotation
Abstract
4.1 Introduction
4.2 Genome assembly algorithms
4.3 Data preprocessing
4.4 Genome assembly approaches: types of assembly
4.5 Tools and software for genome assembly
4.6 Pitfall in genome assemblies
4.7 A mathematical calculation for depth/coverage
4.8 Genome annotation
4.9 Application and future prospects of genome assembly
4.10 Conclusion
Conflict of interest
References
Chapter 5. Computational molecular phylogeny: concepts and applications
Abstract
5.1 Introduction
5.2 Convergent and divergent evolution
5.3 Concept of cladistics and systematics
5.4 Phylogenetic trees’ terminology
5.5 Evolutionary inference of phylogenetic trees
5.6 Tree construction methods
5.7 Estimating reliability of phylogenetic tree
5.8 Phylogenetic tools
5.9 Application of molecular phylogeny
5.10 Conclusion
Conflict of interest
References
Chapter 6. Applications and challenges of microarray and RNA-sequencing
Abstract
6.1 Introduction
6.2 Evolution of microarray
6.3 DNA sequencing
6.4 RNA-sequencing
6.5 Biological databases for data submission
6.6 Applications of microarray
6.7 Applications of RNA-sequencing
6.8 Advantages of transcriptome sequencing over microarray technology
6.9 Limitations and future perspective of RNA-sequencing
6.10 Conclusion
Conflict of interest
References
Chapter 7. RNA-seq for revealing the function of the transcriptome
Abstract
7.1 Introduction
7.2 Next-generation sequencing platforms and their technologies
7.3 Analyzing the RNA-seq data
7.4 RNA-seq applications
7.5 Databases and software for small RNA analysis
7.6 Conclusion
Conflict of interest
References
Chapter 8. Analysis of SSR and SNP markers
Abstract
8.1 Introduction
8.2 Analysis of SSR markers
8.3 Analysis of SNP markers
8.4 Conclusion
Acknowledgments
Conflict of interest
References
Further reading
Chapter 9. Gene Ontology: application and importance in functional annotation of the genomic data
Abstract
9.1 Background
9.2 Gene Ontology–based classification
9.3 Annotation of unknown gene/genome
9.4 GO enrichment analysis
9.5 Applications
9.6 Future prospects
9.7 Conclusion
Acknowledgment
Conflict of interest
Author contributions
References
Chapter 10. Metagenomics: the boon for microbial world knowledge and current challenges
Abstract
10.1 Introduction: an overview of metagenomics
10.2 Resources in metagenomics
10.3 Challenges in metagenomics
10.4 The workflow in metagenome analysis
10.5 Dataset acquire and processing
10.6 Quality control analysis
10.7 Genome assembly tools in metagenomics
10.8 Binning tools in metagenomics
10.9 Data storage and sharing
10.10 Metagenomics analysis: a case study
10.11 Material, methodology, and outcome
10.12 Advantages of metagenomics study
10.13 Limitations and future perspective
10.14 Conclusion
Conflict of interest
References
Chapter 11. Protein structure prediction
Abstract
11.1 Introduction
11.2 Protein structure prediction
11.3 Method of protein structure prediction
11.4 Evaluation of predicted protein structure
11.5 Applications of structure prediction
11.6 Conclusion
Conflict of interest
References
Further reading
Chapter 12. Structural and functional analysis of protein
Abstract
12.1 Protein preliminaries
12.2 Growth of the protein structural database
12.3 Structural topology and fold classification scheme
12.4 D-Structure quality assessment protocol
12.5 Protein 3D structure prediction
12.6 Machine learning in PSP
12.7 Conclusion
Conflict of interest
References
Chapter 13. Computational approaches in drug designing
Abstract
13.1 Introduction
13.2 Computer-aided drug designing
13.3 Computational approaches
13.4 Limitations
13.5 Recent trends in drug designing
13.6 Conclusion
Conflict of interest
References
Chapter 14. Structure-based drug designing
Abstract
14.1 Introduction
14.2 Background of structure-based drug design
14.3 Process of SBDD
14.4 Recent development in SBDD
14.5 Challenges and limitations
14.6 Future prospective
14.7 Conclusion
Conflict of interest
References
Chapter 15. Ligand-based drug designing
Abstract
15.1 Introduction
15.2 Pharmacophore
15.3 3D fingerprints
15.4 Pharmacophore mapping
15.5 Pharmacophore classifications
15.6 Application of pharmacophore in virtual screening and de novo design
15.7 Advancement in exploring 3D pharmacophore principles over the above limitations
15.8 Quantitative structure–activity relationship
15.9 Development of new QSAR: HQSAR
15.10 Application of QSAR/SAR
15.11 Conclusion
Conflict of interest
References
Chapter 16. Discovery and optimization of lead molecules in drug designing
Abstract
16.1 Introduction
16.2 Principles of CADD
16.3 Discovery of the lead molecule
16.4 Types of lead molecules
16.5 Lead optimization and strategies
16.6 Computational lead optimization
16.7 Advantages of computational lead designing
16.8 Future perspectives
16.9 Conclusion
Conflict of interest
References
Chapter 17. Pharmacophore modeling and its applications
Abstract
17.1 Introduction
17.2 Basics of pharmacophore modeling
17.3 Different methods of pharmacophore generation
17.4 Validation of pharmacophore models
17.5 Recent trends in pharmacophore generation
17.6 Applications of pharmacophore modeling
17.7 Future perspectives of pharmacophore models
17.8 Conclusion
Conflict of interest
References
Chapter 18. Molecular docking and molecular dynamics simulation
Abstract
18.1 Introduction
18.2 Molecular docking
18.3 Docking methodologies
18.4 Molecular dynamics simulation
18.5 Challenges in molecular docking and MD simulation techniques
18.6 Conclusion
Conflict of interest
References
Chapter 19. Pharmacokinetics and pharmacodynamics analysis of drug candidates
Abstract
19.1 Introduction
19.2 Postgenomic era and drug discovery
19.3 Pharmacokinetics
19.4 Pharmacodynamics
19.5 Computational approaches for ADMET prediction
19.6 Translational bioinformatics
19.7 Drug repurposing
19.8 Role of pharmacogenomics in precision medicine
19.9 Chemical diversity of natural products: a source for computer-aided drug discovery
19.10 Conclusion
Conflict of interest
References
Further reading
Chapter 20. Computational approaches for vaccine designing
Abstract
20.1 Introduction
20.2 Antigen selection and immunological databases
20.3 In silico method for B-cell epitope prediction
20.4 In silico method for T-cell epitope prediction
20.5 Adjuvant and linker selection
20.6 Building 3D model and validation of fusion vaccine construct
20.7 Miscellaneous properties
20.8 Role of next-generation sequencing technology in vaccine design
20.9 Computer-aided vaccine development example
20.10 Conclusion
Acknowledgments
Conflict of interest
References
Chapter 21. Metabolomics and flux balance analysis
Abstract
21.1 Introduction
21.2 Definition of metabolomics
21.3 MS- and NMR-based techniques in metabolomics
21.4 Data processing in metabolomics
21.5 Applications of metabolomics
21.6 Flux balance analysis
21.7 Metabolic networks and model construction
21.8 Metabolic control analysis and isotopic steady state/carbon flux analysis
21.9 Some important tools of flux balance analysis
21.10 Applications, challenges, and future perspectives of FBA
21.11 Case study: applications of metabolomics and flux balance analysis in industrially important microorganisms
21.12 Conclusion
References
Chapter 22. Topological parameters, patterns, and motifs in biological networks
Abstract
22.1 Introduction
22.2 Biological networks
22.3 Network motifs and patterns
22.4 Analysis of biological network
22.5 Topological parameters
22.6 Biological significance of network motifs
22.7 Applications of network biology
22.8 Limitations and challenges
22.9 Conclusion
Conflict of interest
References
Chapter 23. Network biology and applications
Abstract
23.1 Introduction to biological networks
23.2 Biological networks properties
23.3 Types of biological networks
23.4 Experimental methods in network biology
23.5 Resources for biological network-based studies
23.6 Tools for network pathway analysis
23.7 Applications of network biology
23.8 Challenges and future perspective
23.9 Conclusion
Conflict of interest
References
Chapter 24. Pathway modeling and simulation analysis
Abstract
24.1 Introduction
24.2 Computational modeling of a pathway
24.3 General diagram and language used in pathway modeling
24.4 Pathway simulations analysis
24.5 Platforms used for modeling and simulations
24.6 Applications of pathway modeling and simulations
24.7 Challenges
24.8 Conclusion
Conflict of interest
References
Chapter 25. Systems biology and big data analytics
Abstract
25.1 Introduction
25.2 Big data in general and in the context of biology
25.3 Types of data in systems biology
25.4 Biological big data resources
25.5 Network generation and its analysis from various sources of data
25.6 Big data in drug repurposing and systems pharmacology
25.7 Case study related to transcriptome data analysis
25.8 Limitations in big data analysis
25.9 Conclusion
Acknowledgment
Conflict of interest
References
Chapter 26. Machine learning in bioinformatics
Abstract
26.1 Introduction
26.2 Supervised learning
26.3 Unsupervised machine learning
26.4 Problems to understand supervised learning and unsupervised learning
26.5 Regression
26.6 Clustering
26.7 Unsupervised learning in bioinformatics
26.8 Application of machine learning
26.9 Discussion
26.10 Conclusion
Conflict of interest
References
Chapter 27. Bioinformatics and biological data mining
Abstract
27.1 Biological data mining
27.2 Data mining applications
27.3 Data mining process
27.4 Feature selection technique in data mining
27.5 Major data mining algorithms applicable to biological data
27.6 Biological data evolution and related issues
27.7 Bioinformatics research areas and tools
27.8 Limitations
27.9 Conclusion
Conflict of interest
References
Index

Dev Bukhsh Singh

Dr. Dev Bukhsh Singh is currently an Assistant Professor in the Department of Biotechnology at Siddharth University, Kapilvastu, Siddharth Nagar, India since 2021. He also served as Assistant Professor in the Department of Biotechnology at Chhatrapati Shahu Ji Maharaj University, Kanpur, India from 2009-2021. He received BSc (Biology) and MSc from the University of Allahabad, an MTech from the Indian Institute of Information Technology, Prayagraj India, and a PhD in Biotechnology from Gautam Buddha University, India. He has been actively involved in teaching BSc and MSc Biotechnology students since 2009. His areas of research are medicinal biology, lead compound search, and drug design. He published three edited books: Frontiers in Protein Structure, Function, and Dynamics Computer-Aided Drug Design and Bioinformatics: Methods and Applications. He is a member of various national and international academic bodies and is a reviewer for several international journals.

Affiliations and expertise

Assistant Professor, Department of Biotechnology, Siddharth University, Siddharth Nagar, India

Rajesh Kumar Pathak

Rajesh Kumar Pathak completed his BSc from Barkatullah University, Bhopal, MSc from Chhatrapati Shahu Ji Maharaj University, Kanpur, and PhD from Uttarakhand Technical University, Dehradun, India. He has authored several articles in international journals including, Scientific Reports, Computational Biology and Chemistry, OMICS: A Journal of Integrative Biology, Frontiers in Plant Science, 3 Biotech, Journal of Biomolecular Structure and Dynamics, etc. His research interests lie in the areas of the genome and transcriptome assembly and annotation, microarray data analysis, pathway modeling, and network analysis, molecular docking, virtual screening, and molecular dynamics simulation. He has worked as a Teaching Personnel at G. B. Pant University of Agriculture & Technology, Pantnagar, India, and Teaching Assistant at the School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, India.

Affiliations and expertise

Post-Doctoral Researcher at Chung-Ang University, Anseong, Gyeonggi-do, Republic of Korea

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health