Unit 3108: Advanced Bioinformatics

1. Introduction to Advanced Bioinformatics

• Definition and scope of advanced bioinformatics
• Importance in modern biology and medicine
• Applications: genomics, proteomics, systems biology, drug discovery
• Role of computational techniques in biological data analysis
• Overview of bioinformatics pipelines and software tools

2. Next-Generation Sequencing (NGS) Technologies

2.1 Principles of NGS

• High-throughput sequencing overview
• Comparison with Sanger sequencing

2.2 Major Platforms

• Illumina sequencing: technology, workflow, and applications
• Ion Torrent sequencing: semiconductor sequencing principles
• PacBio sequencing: single-molecule real-time (SMRT) sequencing

2.3 Advantages and Limitations

• Read length, accuracy, throughput, cost
• Application scenarios in genomics research

3. Comparative Genomics

• Concepts and goals of comparative genomics
• Genome alignment and annotation techniques
• Identification of conserved and divergent genomic regions
• Applications in evolutionary biology and functional genomics
• Tools and databases (e.g., Ensembl, UCSC Genome Browser)

4. Structural Bioinformatics

4.1 Biological Macromolecule Structures

• Protein and nucleic acid structure fundamentals
• Levels of protein structure: primary to quaternary

4.2 Prediction and Analysis Tools

• Homology modeling and ab initio prediction
• Molecular dynamics simulations
• Structure visualization software (e.g., PyMOL, Chimera)

4.3 Functional Implications

• Structure-function relationships
• Protein-ligand interactions

5. Systems Biology

• Definition and interdisciplinary nature
• Integration of computational and experimental data
• Modeling biological systems: metabolic, signaling, gene regulatory networks
• Tools for systems biology analysis (e.g., Cytoscape, SBML)
• Applications in understanding cellular behavior and disease mechanisms

6. Metagenomics

• Overview of metagenomics and environmental sampling
• DNA extraction and sequencing from microbial communities
• Bioinformatics analysis: taxonomic profiling, functional annotation
• Applications in microbiome studies, ecology, and biotechnology

7. Phylogenetics and Evolutionary Genomics

• Principles of phylogenetic analysis
• Methods: distance-based, maximum parsimony, maximum likelihood, Bayesian inference
• Reconstruction of evolutionary relationships
• Evolutionary genomics to study genetic diversity and adaptation
• Software tools (e.g., MEGA, BEAST, PhyML)

8. Transcriptomics and Gene Expression Analysis

8.1 Transcriptomics Technologies

• RNA-seq: workflow and data analysis
• Microarrays: principles and applications
• Quantitative PCR for gene expression validation

8.2 Data Analysis and Interpretation

• Differential expression analysis
• Regulatory network inference
• Functional enrichment and pathway analysis

9. Network Biology

• Concept of biological networks: PPI, gene regulatory, metabolic
• Network construction and topology analysis
• Identification of key nodes and modules
• Applications in disease mechanisms and biomarker discovery
• Tools and databases (e.g., STRING, BioGRID)

10. Computational Drug Discovery

• Overview of drug discovery pipeline and challenges
• Virtual screening and molecular docking techniques
• Pharmacophore modeling
• Quantitative Structure-Activity Relationship (QSAR) analysis
• Case studies and software tools (e.g., AutoDock, Schrodinger)