Python · Bioinformaticsv1 · client-side runtime

Write bioinformatics Python in the browser.

Four ordered paths through Biopython, HGVS, pandas and NumPy. Every lesson ships a live editor wired to a real Python runtime, with genomics fixtures already mounted — no install, no notebook server.

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paths: 04
modules: 10
lessons: 109
graded: 20

5′ → 3′26 bp · B-form

Curriculum matrix

Four paths, taken in order

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Foundations

How the ecosystem fits together, and how to work in it.

Getting Started4
Core Concepts5

9 lessons2 modules

Python Data Stack

NumPy, pandas, and plotting — the tools everything else sits on.

NumPy18
pandas21
Plotting & Figures14
Library Landscape6

59 lessons4 modules

Bioinformatics Core

Sequences, records, alignments and annotation with Biopython.

Genomics Foundations2
Biopython15

17 lessons2 modules

Clinical Variants

HGVS nomenclature, normalization, and applied variant workflows.

HGVS Nomenclature11
Applied Workflows13

24 lessons2 modules

variants.vcf

##fileformat=VCFv4.2
##reference=GRCh38
#CHROM  POS       ID           REF  ALT  QUAL   FILTER    INFO
chr17   7676154   .            G    A    99.0   PASS      DP=120;AF=0.51
chr17   43093220  rs80357906   C    T    45.2   PASS      DP=88;AF=0.49
chr12   25245350  .            C    T    12.4   LowQual   DP=19;AF=0.21

payload inopen Applied Workflows →

Sandbox

A scratch runtime with the data already mounted.

The same Pyodide worker the lessons use, with no lesson attached. Open it, load a dataset from the side panel, and run.

numpypandasmatplotlibbiopythonhgvsbioutils

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sample.fasta3 transcript excerpts

reads.fastq3 reads + Phred

variants.vcf4 records, GRCh38

counts.tsv6 genes × 4 samples

annotations.gff3TP53 exons + CDS

deseq2_results.tsvlog2FC + padj