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Full Description
Bioinformatics and Computational Biology: Technological Advancements, Applications and Opportunities is an invaluable resource for general and applied researchers who analyze biological data that is generated, at an unprecedented rate, at the global level. After careful evaluation of the requirements for current trends in bioinformatics and computational biology, it is anticipated that the book will provide an insightful resource to the academic and scientific community. Through a myriad of computational resources, algorithms, and methods, it equips readers with the confidence to both analyze biological data and estimate predictions.
The book offers comprehensive coverage of the most essential and emerging topics:
Cloud-based monitoring of bioinformatics multivariate data with cloud platforms
Machine learning and deep learning in bioinformatics
Quantum machine learning for biological applications
Integrating machine learning strategies with multiomics to augment prognosis in chronic diseases
Biomedical engineering
Next generation sequencing techniques and applications
Computational systems biology and molecular evolution
While other books may touch on some of the same issues and nuances of biological data analysis, they neglect to feature bioinformatics and computational biology exclusively, and as exhaustively. This book's abundance of several subtopics related to almost all of the regulatory activities of biomolecules from where real data is being generated brings an added dimension.
Contents
1. Design and analysis of algorithms. 2. Sequence-based algorithms in Computational Biology. 3. Structure-based algorithms in Computational Biology. 4. Exact heuristics and other algorithms in computational biology. 5. Cloud Based Monitoring of Bioinformatics Multivariate Data with Cloud Platforms. 6. Machine learning and deep learning in Bioinformatics. 6. Machine learning and deep learning in Bioinformatics Bioinformatics and computational biology techniques. 7. Quantum Machine Learning for Biological Applications. 8. Integrating Machine learning strategies with multiomics to augment prognosis of chronic diseases. 9. Deep learning piloted drug design: An advantageous alliance. 10. Drug Discovery by Deep Learning and Virtual Screening: Review and Case Study. 11. Gene regulation, DNA and RNA structure and sequencing. 12. Computational prediction of RNA binding proteins: features and models.15.Tools and Techniques in Structural Bioinformatics.16. Biotechnological, Industrial and Biopharmaceutical Research. 16. A Streamline to New face of Drug Discovery by Protein-Protein and Protein-Nucleic Acid Interactions. 17. From Proteins to Networks: Assembly, Interpretation, and Advances. 18. Higher order organization in biological systems: an introduction. 19. Advancement and applications of biomedical engineering in human health care. 20. Clinical Trials in the Realm of Health Informatics. 21. Application of genomics in Novel Microbial species Identification. 22. Next Generation Sequencing Data Analysis. 23. Computational Molecular Evolution: A Detailed View of Phylogenetic Methods. 24. Exploring Multifaceted Applications of Bioinformatics: An Overview. 25. Industrial and Biopharmaceutical Research in Bioinformatics. 26. Biotechnological, Agriculture, Industrial and Biopharmaceutical Research in Bioinformatics.
