front 1 Discrete | back 1 all characters are known, nothing in between |
front 2 Distance | back 2 simpler, no ins/del ex. minimum evolution, goodniss of fit (additive) 1. distance loses information |
front 3 Advantages? | back 3 distance is quicker 1. closer to original data with fewer steps 2. can map traits dirrectlt to different branches where mutations occur + know type of mutation |
front 4 Earliest forms of distance | back 4 allozyme and microsatellite |
front 5 Additive tree | back 5 shows amount of change no root, indicates branching pattern ? |
front 6 Ultametric tree | back 6 shows number of mutations proportional to temporal distance (time?) |
front 7 Clustering | back 7 "recipe" step by step to final tree, same or small set of outcomes reaches an answer |
front 8 Optimality | back 8 very very best method "best apple pie" lol more time and investment close to best answer 1. explicit measure of data/tree 2. compares different hypotheses evaluate every phylogeny to find best one (optimal topology) |
front 9 Neighbor joining + steps | back 9 begin w/ distance matrix group 2 taxa w/ shortest distance create new node calculate distance of each included taxon to new node recalculate distance matrix using new node repeat |
front 10 Parsimony | back 10 simple = best discrete, optimality im assuming in strict parsimony all characters are treated equally similar to JC Jukes-cantor model of evolution since all mutations are the same. |
front 11 Autapomorphy | back 11 ?? do we need to know this |
front 12 Heuristic search? | back 12 swapping pruning and bisection random additions |