Bioinformatics

1. Bioinformatics Tools and Software
   1. Sequence Alignment
      1. Pairwise Alignment
         1. BLAST
            1. Types of BLAST (Blastn, Blastp, Blastx)
            2. Parameters and settings customization
            3. Output interpretation and file format
         2. FASTA
            1. FASTA file structure and conventions
            2. Sequence similarity searching
            3. Differences between FASTA and BLAST
      2. Multiple Sequence Alignment
         1. Clustal Omega
            1. Input requirements and output formats
            2. Algorithm overview
            3. Phylogenetic insights from Clustal
         2. MUSCLE
            1. Accuracy and speed advantages
            2. Iterative refinement strategies
   2. Genomic Analysis
      1. Gene Prediction
         1. Computational models for gene prediction
         2. Annotation of coding and non-coding genes
         3. Comparative gene prediction
      2. Variant Calling
         1. SNP and Indel identification
         2. Tools for quality control in variant calling
         3. Structural variation analysis
   3. Structural Bioinformatics
      1. Protein Structure Prediction
         1. Homology Modeling
            1. Template selection strategies
            2. Model validation methods
         2. Ab initio Modeling
            1. Methods for structure prediction without templates
            2. Applications and limitations
      2. Molecular Visualization Tools
         1. Common visualization software (PyMOL, Chimera)
         2. 3D structure exploration techniques
         3. Integration with databases for additional information
   4. Phylogenetic Analysis
      1. Phylogenetic Tree Construction
         1. Algorithms (Neighbor Joining, Maximum Likelihood)
         2. Bootstrapping and tree confidence
      2. Evolutionary Models
         1. Model selection and parameter estimation
         2. Molecular clock and dating divergence
   5. Data Mining and Machine Learning in Bioinformatics
      1. Machine Learning Techniques
         1. Supervised vs. unsupervised learning
         2. Applications in bioinformatics datasets
         3. Feature selection and dimensionality reduction
      2. Data Mining Applications
         1. Pattern discovery in biological sequences
         2. Integrative analysis of heterogeneous data
         3. Predictive modeling in genomics
   6. Data Management and Integration
      1. Data Formats and Standards
         1. FASTQ, BED, GFF formats
         2. Choosing appropriate data formats for analysis
      2. Data Integration Challenges
         1. Interoperability between different software tools
         2. Challenges in integrating multi-omics data
      3. Workflow Management Systems
         1. Pipelines for reproducible bioinformatics research
         2. Common workflow management tools
   7. Visualization and Interpretation
      1. Visualization Techniques
         1. Graphical representations of sequence alignments
         2. Interactive genomics data visualization
      2. Interpretation of Results
         1. Strategies for translating computational outputs into biological insights
         2. Communicating results to interdisciplinary teams