A self-guided lab notebook · runs in your browser

Bacteriastrains.

A twelve-module course on the resolution level below species — where this site's running example finally gets resolved: commensal E. coli and Shiga-toxin-producing E. coli are the same species, but different strains, distinguished by specific genes. Covers real virulence and resistance genes, plasmids and mobile genetic elements, why probiotic strains aren't interchangeable, and a real cross-validated strain classifier — closing out the full genus → species → strain resolution ladder across all five courses on this site. Runs natively in-browser; no local installation required.

Start the course →
Fig. 1 — Gene signatures by pathotype, this course's data
stx1
stx2
eae
papC
hlyA
blaKPC
EHEC
0.64
0.73
0.86
0.14
0.18
0.23
UPEC
0.00
0.18
0.32
0.68
0.64
0.23
commensal
0.18
0.13
0.18
0.22
0.18
0.31
Fraction of strains (out of 89 synthetic, illustrative E. coli strains) carrying each gene, by pathotype. EHEC's signature is stx1/stx2/eae; UPEC's is papC/hlyA; blaKPC (resistance) stays roughly flat across all three — a real, separate trait, not tied to virulence. Notebook 03 explains every gene; notebook 09 builds a real classifier from exactly this table.

Specimen log — course order

№ 00 Welcome
How this course works, and the new synthetic dataset it introduces
 → № 01 What Is a Strain?
Defining the resolution level below species
 → № 02 Why This Course Needed New Data
No dataset on this site resolves to strain level — until now
hands-on → № 03 E. coli Pathotypes, For Real
Shiga toxin, intimin, and the genes behind EHEC/UPEC
hands-on → № 04 Detecting Strains: Beyond MLST
cgMLST, SNP typing, whole-genome phylogenetics
conceptual → № 05 Plasmids & Mobile Genetic Elements
Why strain traits can move between organisms
hands-on → № 06 Antibiotic Resistance as a Strain Trait
Carbapenem resistance, real and high-stakes
hands-on → № 07 Probiotic Strains Aren't Interchangeable
Clinical evidence is strain-specific, not species-wide
conceptual → № 08 Building a Strain-Level Panel
Same method as the bioinformatics course, one resolution down
hands-on → № 09 Classifying Strains by Function
A real, cross-validated pathotype classifier
hands-on → № 10 What Strain Data Still Can't Tell You
Gene presence vs. gene activity
conceptual → № 11 The Full Resolution Ladder
Closing all five courses out
 →
Nothing to install. Every hands-on notebook here uses only pandas, numpy, and scikit-learn, reading a new but equally lightweight synthetic dataset, ecoli_strain_profiles.csv — no setup cells, no waiting on installs.