Introduction to Computational Biology and Bioinformatics
( 24 Modules )

Module #1
Introduction to Computational Biology
Overview of the field, importance, and applications

Module #2
Biology Basics for Computational Biologists
Review of biological concepts:cells, genes, genomes, and evolution

Module #3
Computational Tools for Biology
Introduction to Linux, command-line interfaces, and scripting

Module #4
Biological Databases
Overview of genomic, transcriptomic, and proteomic databases

Module #5
Sequence Alignment
Introduction to sequence alignment algorithms and tools (e.g. BLAST)

Module #6
Multiple Sequence Alignment
Methods and tools for multiple sequence alignment (e.g. ClustalW)

Module #7
Phylogenetic Analysis
Introduction to phylogenetic trees and inference methods

Module #8
Molecular Evolution
Models of molecular evolution and phylogenetic tree reconstruction

Module #9
Genome Assembly
Overview of genome assembly methods and tools (e.g. Velvet)

Module #10
Genome Annotation
Introduction to genome annotation and functional prediction

Module #11
Functional Genomics
High-throughput sequencing technologies and applications

Module #12
RNA-Seq Analysis
Introduction to RNA-Seq data analysis and differential gene expression

Module #13
ChIP-Seq Analysis
Introduction to ChIP-Seq data analysis and transcription factor binding

Module #14
Microarray Data Analysis
Introduction to microarray data analysis and gene expression profiling

Module #15
Protein Structure Prediction
Introduction to protein structure prediction methods and tools

Module #16
Protein Function Prediction
Introduction to protein function prediction methods and tools

Module #17
Bioinformatics Pipelines
Introduction to bioinformatics pipelines and workflow management

Module #18
Genomic Variation Analysis
Introduction to genomic variation analysis and SNP detection

Module #19
Population Genetics
Introduction to population genetics and genotype-phenotype associations

Module #20
Systems Biology
Introduction to systems biology and network analysis

Module #21
Machine Learning in Bioinformatics
Introduction to machine learning concepts and applications in bioinformatics

Module #22
Visualization in Bioinformatics
Introduction to data visualization tools and techniques in bioinformatics

Module #23
Ethics in Bioinformatics
Discussion of ethical considerations in bioinformatics research and applications

Module #24
Course Wrap-Up & Conclusion
Planning next steps in Introduction to Computational Biology and Bioinformatics career

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