1. Pattern frequency demo
2. Optimizing branch lengths using ML
3. Comparing trees using ML requires branch length optimization
4. Parsimony informative-pattern frequency demo
5. Bootstrapping in phylogenetics
6. Bootstrapping in parsimony-informative pattern frequency space demo
7. How the P-value depends on the per-site likelihood difference distribution
8. Using ML to learn a discrete-state, discrete-time Markov model's parameter value
9. Missing data version of using ML to learn a discrete-state, discrete-time Markov model's parameter value
10. a simple HMM (simulating from and learning parameters of)

Back to the demo table of contents...

Source code at https://github.com/mtholder/mephytis

Thanks to the U.S. National Science Foundation and the Heidelberg Institute for Theoretical Studies for support.