Bioinformatics MasterClass

The full theoretical foundation of bioinformatics, in 31 sections

This is the most comprehensive theory course on the site. Where the hands-on trainings teach you to run a specific analysis, this one explains the reasoning underneath all of them — why alignment algorithms score the way they do, what a substitution matrix encodes, how phylogenetic models differ and what each assumes. Across 31 sections it builds the understanding that makes every applied course easier.

What it covers

• Foundations — what bioinformatics is, and how its branches relate.
• Databases and searching — the major repositories and how to query them effectively.
• Sequence analysis and alignment — pairwise alignment and the algorithms behind it.
• Scoring matrices — what PAM and BLOSUM actually encode, and why the choice changes your results.
• Multiple sequence alignment — methods, and where each breaks down.
• DNA and protein analysis — characterising sequences of both kinds.
• Protein and gene families — grouping by relatedness and function.
• Gene prediction — finding genes in raw genomic sequence.
• Regulatory elements — promoters, enhancers and the sequences that control expression.
• Evolution and phylogenetics — tree construction concepts, phylogenetic models, and building trees properly.

Why theory is worth your time

You can run BLAST without knowing what BLOSUM62 does, and most people do. But when an alignment gives a surprising result, or a reviewer asks why you chose one model over another, the difference between following a tutorial and understanding the method becomes the difference between defending your work and guessing. This course is aimed squarely at that.

What you can do afterwards

Read bioinformatics methods sections critically, choose parameters deliberately rather than by default, and explain why an analysis is set up the way it is. It pairs naturally with any of the hands-on courses, which supply the practice this supplies the reasoning for.

Who it suits

Students on bioinformatics or computational biology programmes, researchers who use these tools daily without having been taught the theory, and anyone preparing for exams or interviews in the field.