Description
Elsevier Bioinformatics Methods and Applications by Dev Bukhsh Singh, Rajesh Kumar Pathak
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. Table of Contents : 1. Introduction to Basics of Bioinformatics2. Biological Databases and their Applications3. Biological Sequence Analysis4. Genome Assembly and Annotation5. Computational Molecular Phylogeny: Concepts and Applications6. Applications and challenges of microarray and RNA-sequencing7. RNAseq Data Analysis8. Analysis of SSR and SNP Markers9. Gene Ontology (GO): Application and Importance in Functional Annotation of the Genomic Data10. Metagenomics: The Boon for Microbial World Knowledge and Current Challenges11. Protein structure Prediction12. Structural and Functional analysis of protein13. Computational Approaches in Drug designing14. Structure-Based Drug Designing15. Ligand-Based Drug Designing16. Discovery and Optimization of Lead Molecules in Drug Designing17. Pharmacophore modeling and its applications18. Molecular Docking and Molecular Dynamics Simulation19. Pharmacokinetics and Pharmacodynamics analysis of Drug Candidates20. Computational Approaches for Vaccine Designing21. Metabolomics and Flux Balance Analysis22. Topological Parameters, Patterns, and Motifs in Biological Networks23. Network Biology and its Application24. Pathway Modeling and Simulation Analysis25. Systems Biology and Big Data Analytics26. Machine Leaning in Bioinformatics27. Bioinformatics and Biological Data mining