fitch optimization
down pass
up pass
assigning state to nodes and conditional states
Generalized parsimony
infer phylogenies and calculate large data sets indentical changes (JC)
Maximum likelihood
uses models of evolution and stratistical tests
computationally intense
discrete, optimality
Likelihood = data | hypothesis
probability of data given a certain hypothesis
Two ways to get a known phylogeny to test effectiveness of phylogenetic analyses
Use know phylogenies, ex. bacteria culture experiments
simulate data sets
3 types of statistical tests ML analysis can do ?
is the model valid?
molecular clock - untrametric evo, chage rate = same, estimate divergence time and count up all mutations ?
which tree is best?
3 disadvantages of ML analyses
circularity - need a phylogeny to infer
computationally intense
difference in rate of evolution (heteroachy) - won't be realistic
Six criteria for evaluating effectiveness
efficiency
power
consistency
robustness
falsifiability (testability)
ideological?
congruence of methods
When changes are relatively rare (data set not saturated) both methods support the same topology