OUTLINE for book chapters.docx

**[PHYLOGENETICS]** **[1. Introduction to Phylogenetics]** - Definition and Scope - What is phylogenetics? - Explanation of phylogenetics as the study of evolutionary relationships among species or genes. - Scope and applications in various biological fields....

**[PHYLOGENETICS]** **[1. Introduction to Phylogenetics]** - Definition and Scope - What is phylogenetics? - Explanation of phylogenetics as the study of evolutionary relationships among species or genes. - Scope and applications in various biological fields. - Role in understanding biodiversity, evolutionary biology, systematics, and comparative genomics. - Historical Development - Early concepts and pioneers in phylogenetics. - Contributions of Charles Darwin, Willi Hennig, and others. - Milestones in the development of phylogenetic methods. - Introduction of molecular data, the development of computational methods, and the impact of genomic data. - Importance in Evolutionary Biology - Role in understanding evolutionary relationships. - How phylogenetics helps elucidate the tree of life and the history of life on Earth. - Contributions to taxonomy, systematics, and biodiversity studies. - Impact on the classification and conservation of species. **[2. Fundamental Concepts]** - Evolutionary Trees and Networks - Phylogenetic Trees - Types of trees (rooted, unrooted, cladograms, phylograms). - Interpretation and significance of tree topology. - Phylogenetic Networks - Definition and differences from trees. - Applications in depicting reticulate evolution, such as hybridization and horizontal gene transfer. - Basic Terminology - Nodes, Branches, and Leaves - Definitions and roles in tree structure. - Internal vs. terminal nodes. - Monophyly, Paraphyly, and Polyphyly - Definitions and examples. - Importance in classification and evolutionary studies. - Models of Evolution - Molecular Evolution Models - Jukes-Cantor model: assumptions and applications. - Kimura two-parameter model: differences and significance. - Morphological Evolution Models - How morphological traits evolve and are used in phylogenetic analysis. - Examples of models used in morphological studies. **[3. Data Types and Sources]** - Molecular Data - DNA, RNA, and Protein Sequences - Methods of collection, sequencing technologies. - Applications in phylogenetic analysis. - Genomic and Metagenomic Data - Techniques for acquiring and assembling genomic data. - Challenges and advantages of metagenomic data. - Morphological Data - Collection and analysis of morphological traits. - Integration with molecular data for comprehensive phylogenies. - Behavioural and Ecological Data - Importance and methods of including behavioural and ecological traits. - Fossil Data - Methods for integrating fossil records into phylogenetic studies. - Challenges and case studies. - Integrative Data Approaches - Combining different types of data (e.g., molecular, morphological, ecological) for robust phylogenetic analyses. **[4. Methods of Phylogenetic Inference]** - Distance-Based Methods - UPGMA (Unweighted Pair Group Method with Arithmetic Mean) - Methodology, assumptions, and applications. - Neighbor-Joining - How it works, advantages over UPGMA, and use cases. - **Character-Based Methods** - Maximum Parsimony - Principles, strengths, and limitations. - Maximum Likelihood - Concepts, computational strategies, and advantages. - Bayesian Inference - Bayesian frameworks, MCMC (Markov Chain Monte Carlo) methods, and software tools. - **Comparative Methods** - Gene Tree vs. Species Tree - Explanation and significance of discrepancies between gene trees and species trees. - Coalescent Theory - Basics, applications in phylogenetics, and impact on understanding evolutionary history. **[5. Model Selection and Testing]** - **Model Selection Criteria** - Akaike Information Criterion (AIC) - Concept, calculation, and use in model comparison. - Bayesian Information Criterion (BIC) - Differences from AIC and applications. - **Hypothesis Testing in Phylogenetics** - Likelihood Ratio Tests - Implementation, interpretation, and examples. - Bootstrap Analysis - Methodology, significance, and how to perform bootstrap analysis. - Bayesian Posterior Probabilities - Principles, calculation, and interpretation in Bayesian phylogenetics. **[6. Computational Tools and Software]** - **Software for Phylogenetic Analysis** - **MEGA (Molecular Evolutionary Genetics Analysis)** - Features, usage, and examples. - **BEAST (Bayesian Evolutionary Analysis Sampling Trees)** - Capabilities, setup, and case studies. - **MrBayes** - Overview, command-line and GUI usage, examples. - **RAxML (Randomized Axelerated Maximum Likelihood)** - High-performance features, installation, and examples. - *PAUP (Phylogenetic Analysis Using Parsimony)* \* - Key features, usage, and applications. - **High-Performance Computing in Phylogenetics** - Importance of HPC in handling large datasets and complex models. - Examples of HPC resources and software optimizations. - **Workflow Automation and Reproducibility** - Best practices for automating phylogenetic workflows. - Tools for ensuring reproducibility in phylogenetic analyses. **7. Phylogenomics** Concept and Scope Genomic Data Acquisition and Assembly Alignments and Orthology Assessment Concatenated vs. Coalescent-Based Approaches Case Studies in Phylogenomics **[8. Phylogenetic Comparative Methods]** - Ancestral State Reconstruction - Techniques for reconstructing ancestral states of traits. - Applications and examples. - Comparative Analysis of Trait Evolution - Methods for analyzing trait evolution across phylogenies. - Statistical techniques and software tools. - Correlation and Causation in Evolutionary Traits - Approaches to distinguish between correlation and causation. - Phylogenetic Signal and Noise - Identifying and addressing phylogenetic signal and noise in data. **9. Advanced Topics in Phylogenetics** - **Horizontal Gene Transfer** - Detection methods and implications for phylogenetic analysis. - **Hybridization and Introgression** - Impact on evolutionary relationships and methods for detection. - **Phylogenetic Networks and Reticulate Evolution** - Advanced concepts, methodologies, and examples. - **Molecular Clock Hypothesis** - Theory, applications, and differences between relaxed and strict clocks. - **Host-Parasite Coevolution** - Case studies and methodological approaches for studying coevolution. **10. Applications of Phylogenetics** - Biodiversity and Conservation - Role in conservation biology. - Epidemiology and Public Health - Phylogenetics of Pathogens - Understanding the spread and evolution of diseases. - Biogeography - Phylogenetic insights into geographical distributions. - Functional and Ecological Genomics - Integrating phylogenetics with functional genomics. 11\. Challenges and Future Directions - Big Data and Phylogenetics - Handling large datasets. - Integrating Multi-Omics Data - Combining genomics, transcriptomics, proteomics. - Emerging Technologies - Impact of CRISPR, single-cell sequencing, etc. - Ethical and Societal Implications - Ethical considerations in phylogenetic research. **Star points** *Advantage and disadvantages* *Practical Example in each chapter* *MCQ questions and theory questions* *Applications* [ **STRUTURAL BIOINFROMATICS AND DRUG DESIGNING** ] **1. Introduction to Structural Bioinformatics and Drug Design** - **Definition and Scope** - Overview of structural bioinformatics. - Importance in drug design and development. - **Historical Development** - Key milestones in structural bioinformatics and drug design. - **Relevance to Bioinformatics** - Integration with bioinformatics tools and techniques. **2. Fundamental Concepts in Structural Bioinformatics** - **Protein Structure Basics** - Levels of protein structure (primary, secondary, tertiary, quaternary). - Importance of protein folding and stability. - **Nucleic Acid Structures** - DNA and RNA structure and function. - **Macromolecular Interactions** - Protein-protein, protein-DNA, and protein-ligand interactions. - **Structure-Function Relationship** - How structure determines function in biological macromolecules. **3. Structural Data Acquisition and Sources** - **Experimental Techniques** - X-ray Crystallography - Principles, workflow, and data interpretation. - Software: CCP4, PHENIX. - Nuclear Magnetic Resonance (NMR) Spectroscopy - Principles, workflow, and data interpretation. - Software: NMRPipe, CYANA. - Cryo-Electron Microscopy (Cryo-EM) - Principles, workflow, and data interpretation. - Software: RELION, CryoSPARC. - **Databases for Structural Data** - Protein Data Bank (PDB) - Structure retrieval and analysis. - Other databases (e.g., RCSB PDB, PDBe, PDBj). - Nucleic acid databases (e.g., NDB - Nucleic Acid Database). **4. Computational Tools and Techniques in Structural Bioinformatics** - **Molecular Visualization** - Tools: PyMOL, Chimera, Jmol. - Techniques for visualizing and analyzing macromolecular structures. - **Molecular Dynamics Simulations** - Principles and applications in studying protein dynamics. - Software: GROMACS, AMBER, NAMD. - **Homology Modeling** - Techniques for predicting protein structures from homologous sequences. - Software: MODELLER, SWISS-MODEL. - **Protein Structure Prediction** - Ab initio and template-based modeling. - Software: AlphaFold, Rosetta. - **Docking Simulations** - Principles of molecular docking. - Software: AutoDock, DOCK, Glide. **5. Structure-Based Drug Design (SBDD)** - **Principles of SBDD** - Concept of target-based drug discovery. - Role of structural information in drug design. - **Lead Identification and Optimization** - Methods for identifying and optimizing lead compounds. - Virtual screening techniques. - **Drug-Target Interactions** - Understanding and predicting binding sites. - Techniques for assessing binding affinity. - **Computational Techniques in SBDD** - Ligand-based vs. structure-based methods. - Software: Schrödinger Suite, MOE (Molecular Operating Environment). **6. Bioinformatics Approaches in Drug Design** - **Sequence Analysis and Alignment** - Role in identifying potential drug targets. - Software: BLAST, Clustal Omega. - **Functional Genomics and Proteomics** - Techniques for identifying drug targets and pathways. - **Pharmacophore Modeling** - Principles and applications in drug design. - Software: Phase, LigandScout. - **Quantitative Structure-Activity Relationship (QSAR)** - Techniques for predicting the activity of drug compounds. - Software: QSAR Toolbox, ChemOffice. **7. Case Studies in Structural Bioinformatics and Drug Design** - **Case Study 1: HIV Protease Inhibitors** - Structural analysis and drug design process. - Key software and methodologies used. - **Case Study 2: G Protein-Coupled Receptors (GPCRs)** - Challenges and successes in structure-based drug design. - **Case Study 3: COVID-19 Therapeutics** - Structural biology insights into SARS-CoV-2. - Drug design strategies and software tools used. **8. Challenges and Future Directions** - **Challenges in Structural Bioinformatics** - Data quality and completeness. - Computational limitations and accuracy. - **Innovations and Emerging Technologies** - Advances in cryo-EM and AI-based predictions (e.g., AlphaFold). - **Future of Drug Design** - Integrating multi-omics data. - Personalized medicine and structure-based drug design. **9. Practical Applications and Software Tutorials** - **Practical Example: Homology Modelling** - Step-by-step guide using MODELLER. - **Practical Example: Molecular Docking** - Step-by-step guide using AutoDock. - **Practical Example: Molecular Dynamics Simulation** - Step-by-step guide using GROMACS. - **Practical Example: Virtual Screening** - Step-by-step guide using Schrödinger Suite. **Star points**