Genomic Data Analysis with R and Bioconductor

Topic 1: Introduction to Bioconductor and  Sequence Analysis

Overview of Bioinformatics

Understanding Sequence Alignment

Introduction to Bioconductor

Multiple Sequence Analysis

Interpreting Sequence Similarity Scores

Topic 2: Structural Bioinformatics and Variant Calling 

Introduction to Structural Bioinformatics

Analysing Protein Structures

Variant Calling Using Bioconductor

Evaluating Relationships Between Protein Structures and Functions

Topic 3: Transcriptomes, Genomics, and Variant Analysis 

Introduction to Transcriptome Data Analysis

Genomic Data Analysis and Visualization

Gene Expression Analysis and Differential Expression

Variant Detection and Annotation in Genomic Data

Topic 4: Machine Learning for Bioinformatics 

Introduction to Machine Learning

Machine Learning for Predictive Modelling in Bioinformatics

Clustering and Classification of Biological Data

Predictive Models for Genomic and Transcriptomic Data

Topic 5: Data Visualization for Bioinformatics 

Creating Data Visualizations using ggbio

Heatmaps for Transcriptomic and Genomic Data

Visualizing Biological Pathways and Networks

Communicating Biological Insights through Effective Visualizations