Functional Genomics

1. Transcriptomics: Analysis of the expression and regulation of genes at the transcript level.
   • Bulk RNA analysis
     • Filtering low-count genes
     • Normalization
     • Effect Size Estimation
     • Differential expression and its statistics
   • Sc Analysis
     • Filtering out low-quality cells and correcting noise
     • Normalizing data and stabilising variances
     • Removing confounding sources of variation
     • Selecting informative features and reducing dimensionality
     • Creating cell clusters and mapping them to specific cell identities
     • Performing differential gene expression analysis
     • Deciphering changes in cell composition and inferring cellular perturbations
     • Investigating cellular communication pathways
2. Proteomics: Analysis of protein expression. Most of the things you learn in Sc/Bulk RNA-seq analysis apply here.
3. Metabolomics: Metabolite profiling and metabolic fingerprinting

Structural Bioinformatics

In this track, you will learn:

1. Public repositories of structural data
2. UniProt and basic Sequence alignment tools
3. Protein structure analysis
4. Protein structure prediction and docking
5. Drug discovery

Genomic Epidemiology

Genomic epidemiology in this track you will learn how to combine genomic data with traditional epidemiological methods to understand pathogen evolution, track disease outbreaks, and inform public health strategies, enhancing the ability to control and prevent diseases.

Knowledge-Based Bioinformatics

This Track is from our research unit, and it’s tailored for individuals or groups engaging in bioinformatics projects seeking a comprehensive understanding of the entire analysis-to-interpretation workflow. It's an immersive journey designed to empower participants to confidently navigate every aspect of their projects.