A self-guided lab notebook · runs in your browser

Species-levelresolution.

A twelve-module course on what a bacterial species actually is — the ANI convention that defines one, real ongoing reclassification work happening inside genera already covered on this site, and exactly where species-level data stops being enough (a single species, E. coli, contains both harmless commensals and dangerous pathogens). Reuses the bioinformatics course's already-species-level dataset throughout. Runs natively in-browser; no local installation required.

Start the course →
Fig. 1 — Taxonomic resolution across this site's courses
Genus
course 3
→
Species
this course
→
Strain
coming later
Each step down needs a harder method to actually measure (16S → shotgun/MetaPhlAn3 → whole-genome ANI → strain typing) and resolves a real blind spot the step above couldn't see — and creates a new one exactly where the next step picks up.

Specimen log — course order

№ 00 Welcome
How this course works, reusing the bioinformatics course's data
 → № 01 What Makes a Species?
ANI, why 16S can't resolve this far, species as a convention
 → № 02 This Course's Data, at Species Resolution
Re-examining familiar genera one level down
hands-on → № 03 The Faecalibacterium Split
Real, ongoing taxonomic reclassification
hands-on → № 04 Bifidobacterium Species
Infant- vs. adult-associated species
hands-on → № 05 Akkermansia Beyond muciniphila
The genus has more than one member
hands-on → № 06 E. coli and the Pathotype Problem
One species, wildly different outcomes — the bridge to strains
hands-on → № 07 Bacteroides & Prevotella Species
No dataset here resolves this far — real research only
conceptual → № 08 How Species Boundaries Are Measured
ANI, MLST, whole-genome vs. marker-gene methods
conceptual → № 09 Is "Species" a Natural Category?
Horizontal gene transfer and the contested species concept
conceptual → № 10 Species-Level Diversity, Hands-On
Shannon & Simpson, by hand, done correctly at this resolution
hands-on → № 11 Species Isn't the End Either
Closing, and the hand-off to a future strains course
 →
Nothing to install. Every hands-on notebook here uses only pandas, numpy, and scipy, and reads toy_species_abundance.csv directly from the bioinformatics course — no new datasets, no setup cells.