Study library
Study topics: learn it, see it, code it
In-depth topics that take you from the molecules to real analyses. Each one combines a written lesson with diagrams and interactive 3D structures, Python you run in your browser on real data, a knowledge check and a mini project.
- LessonClear explanations with accurate chemical and biological diagrams.
- 3D and interactiveReal crystal structures and explainers you can explore.
- Code labPython runs in your browser on real public datasets. Nothing to install.
- Check and projectA scored quiz and a guided mini project, with progress saved.
Level 1 · Explorer
Foundations
Understand the biology and the questions before the tools.
- 1.1Available DNA, RNA and the central dogma Nucleotides, base pairing and the double helix in real 3D structures, how RNA differs, and how a gene becomes a protein. Your first Python runs on a real viral genome. About 90 min
- 1.2Available Genes, genomes and chromosomes How genomes are organised, what a gene and a transcript are, and how to read a genome annotation. About 90 min
- 1.3Available Proteins: from amino acids to 3D structure Amino acid chemistry, the four levels of protein structure and why structure determines function. About 90 min
- 1.4Available Mutations and genetic variation SNVs, indels and structural variants, how variants are named in VCF and HGVS, and what they do to genes and proteins, with real ClinVar and 1000 Genomes data. About 90 min
- 1.5Available Gene expression and regulation The lac operon, promoters, enhancers and transcription factors, chromatin, splicing and RNA-seq counts: how cells control which genes are on. About 90 min
- 1.6In preparation Experimental design and statistics essentials Replicates, controls, confounders, p-values, effect sizes and multiple testing, with simulations you can run.
Level 2 · Practitioner
Code & compute
Become fluent with the command line, Python, R and Git.
- 2.1In preparation The Linux command line for biologists Files, paths, permissions and the core commands for inspecting large biological files.
- 2.2In preparation Text processing and Bash scripting grep, cut, sort, awk and pipes on FASTA, GFF and VCF files, then safe, reusable scripts.
- 2.3In preparation Python for biological data Variables, loops, functions and files, then algorithms such as k-mer counting and ORF finding.
- 2.4In preparation Data analysis with pandas, NumPy and plots Load, clean, summarise and plot tables such as a real RNA-seq count matrix.
- 2.5In preparation R, the tidyverse and Bioconductor Data frames, dplyr and ggplot2, and the Bioconductor objects used in omics analysis.
- 2.6In preparation Git, GitHub and reproducible code Commits, branches, pull requests and a README that lets others rerun your work.
Level 3 · Sequence Analyst
Sequence data
Read, check and align real sequencing data.
- 3.1In preparation Sequencing technologies Sanger, Illumina, PacBio and Nanopore: how each works, its error profile and when to use it.
- 3.2In preparation File formats and coordinates in practice Parse FASTA, FASTQ, GFF and VCF yourself and never be caught out by 0-based versus 1-based coordinates.
- 3.3In preparation Read quality control and trimming Phred scores, adapter content and quality plots on real E. coli reads, and when to trim.
- 3.4In preparation Sequence alignment algorithms Needleman–Wunsch, Smith–Waterman and scoring matrices, implemented step by step.
- 3.5In preparation Read mapping, SAM and BAM How short-read aligners work, what each SAM field means and how to judge an alignment.
- 3.6In preparation BLAST and biological databases NCBI, ENA, Ensembl and UniProt; accessions, programmatic access and reading BLAST results.
Level 4 · Omics Analyst
Omics analysis
Turn data into defensible biological answers.
- 4.1In preparation RNA-seq: from reads to counts Library types, alignment versus pseudoalignment, and building a count matrix.
- 4.2In preparation Differential expression and enrichment Normalisation, the negative binomial model and enrichment, on the real pasilla dataset.
- 4.3In preparation Variant calling and annotation From aligned reads to filtered, annotated variants, and what a call can and cannot tell you.
- 4.4In preparation Single-cell RNA-seq Cell QC, normalisation, clustering and marker genes, and the pitfalls specific to single cells.
- 4.5In preparation Epigenomics and gene regulation ChIP-seq, ATAC-seq and DNA methylation: peaks, signal tracks and their interpretation.
- 4.6In preparation Proteomics and metabolomics Mass spectrometry, peptide identification and quantification, and the main sources of error.
Level 5 · Pipeline Engineer
Workflows & scale
Make analyses repeatable, portable and scalable.
- 5.1In preparation Software environments with conda Install bioinformatics tools from Bioconda and pin versions so analyses rerun exactly.
- 5.2In preparation Containers: Docker and Apptainer Package an analysis with its software and run it on a laptop or a cluster.
- 5.3In preparation Workflows with Snakemake Rules, wildcards and a dependency graph that reruns only what changed.
- 5.4In preparation Nextflow and nf-core Processes and channels, and running community pipelines with test data.
- 5.5In preparation HPC and the Slurm scheduler Submit, monitor and size jobs responsibly on a shared cluster.
- 5.6In preparation Cloud computing and data management Storage, costs, data transfer and the FAIR principles for sharing data.
Level 6 · Research Scientist
AI, research & career
Specialise, use machine learning responsibly and present your work.
- 6.1In preparation Machine learning for biological data Features, baselines, linear models and trees on real omics data.
- 6.2In preparation Model evaluation and data leakage Splits, cross-validation, imbalance and the leakage traps that inflate published results.
- 6.3In preparation Deep learning for sequences and structures Neural networks for sequence data, and what AlphaFold predictions do and do not tell you.
- 6.4In preparation Multi-omics integration Combine expression, methylation and mutation data without fooling yourself.
- 6.5In preparation Structural bioinformatics Protein structures, the PDB, structure comparison and docking basics.
- 6.6In preparation Research practice, communication and careers Reproducible reports, figures, writing, and turning projects into a portfolio.