How does biological complexity emerge?
Investigate it yourself. Set the parameters, run the simulations, inspect the formulas and follow the citations. The Lab doesn't hand you a verdict: it shows which assumptions drive the answer.
No account needed. Everything runs in your browser, and every run can be repeated from its seed.
Explore the probabilities
Change the building blocks, sequence length, population, mutation rate and selection, and compare three models that make different assumptions. Then run a seeded Monte Carlo simulation and watch.
Open the simulator →IIInvestigate the molecules
Fold a protein on a lattice, take a bacterial flagellum apart, mutate the human β-globin gene, and turn the rotor of ATP synthase.
Choose a molecule →IIIExamine the evidence
For each case: what is observed, what evolutionary theory proposes, what remains unresolved, and which evidence would settle it. Every claim is labelled established, active or speculative.
Read the evidence →What the Lab does
It is a set of working models you can run in your browser. Each one takes a claim that comes up in debates about evolution, turns it into numbers you can change, and shows you the result alongside the formula and the published evidence. None of them gives a verdict. They show you which assumptions the answer depends on.
- Probability Simulator
- Asks how long it takes to hit one particular DNA or protein sequence. Shows three answers: pure random guessing, an idealised selection ratchet, and a real population with mutation, selection and chance. The gap between them is the lesson: "one in 10 to the power N" is the answer for guessing, not for evolution, and the realistic answer depends heavily on whether the steps along the way are useful.
- Genetic entropy
- Asks whether harmful mutations pile up faster than selection removes them. You set how many new mutations each person gets, how harmful they are, how big the population is and whether there is sex, then follow thousands of generations and see whether fitness holds steady, slowly declines or collapses.
- Protein folding
- Lets you build a short protein on a grid and see every shape it could fold into, to show what makes a sequence fold into one stable shape and how rare such sequences might be.
- Flagellum
- Lets you take apart a 3D model of a bacterial motor part by part and read what each part does, what happens without it, and what it resembles elsewhere in the cell.
- DNA explorer
- Lets you edit the human β-globin gene (it codes for one of the two kinds of chain in haemoglobin) letter by letter, and see which changes are silent, which alter the protein, and which break it, with known disease mutations for comparison.
- Molecular machines
- Lets you turn the rotor of ATP synthase, the cell's energy turbine, and watch kinesin walk along its track, with the measured numbers for each.
- Evidence
- Collects, for every case, what has been observed, what evolutionary theory proposes, what is still unresolved, and which evidence would settle it, with each claim labelled established, active or speculative, and every source cited.
Four different questions
They are often run together in debate. The Lab treats them separately and says which one each module addresses.
Biological evolution
Change in populationsHeritable change in populations over generations: mutation, selection, drift, recombination. Much of it is observed directly (antibiotic resistance, the Lenski lines). The open questions are about scale, rate and sufficiency.
The origin of life
Life from non-lifeHow the first self-replicating, metabolising system arose from chemistry. Evolution by natural selection needs a replicator to act on, so it cannot explain its own starting point. This Lab does not model abiogenesis.
The origin of biological information
New genes, new foldsWhere the specific sequences in genes and proteins come from, especially genuinely new genes and protein folds rather than variations of existing ones.
The emergence of molecular machines
Many parts, one functionHow systems of many interacting proteins (motors, pumps, secretion systems) came to be, and whether every intermediate could have been useful.
How the Lab works
- Separate models, not one master number. Blind random sampling, an idealised selection ratchet and population genetics answer different questions, and they are shown side by side.
- Every formula on screen. Each result shows its formula and variables, and whether it is exact, a bound or an approximation.
- Reproducible. Simulations run on a seeded random-number generator; share the link and anyone gets the same run.
- Sourced values. Mutation rates, population sizes and functional fractions come from cited measurements, or are labelled illustrative.
- Labelled certainty. Each evidence claim is marked established, active research or speculative, and the citations are to the primary literature, with books flagged as books.
- Not a proof. The Lab is for investigation. Evolution Issues sets out its own perspective on the About page; the Lab is built to be useful whatever yours is.