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The Contest Between Parsimony and Likelihood

2004; Oxford University Press; Volume: 53; Issue: 4 Linguagem: Inglês

10.1080/10635150490468657

1076-836X

Elliott Sober,

Biomedical Text Mining and Ontologies

In a “classic” phylogenetic inference problem, the observed taxa are assumed to be the leaves of a bifurcating tree and the goal is to infer just the “topology” of the tree (i.e., the formal tree structure linking the extant taxa at the tips), not amount of time between branching events, or amount of evolution that has taken place on branches, or character states of interior vertices. Two of the main methods that biologists now use to solve such problems are maximum likelihood (ML) and maximum parsimony (MP); distance methods constitute a third approach, which will not be discussed here. ML seeks to find the tree topology that confers the highest probability on the observed characteristics of tip species. MP seeks to find the tree topology that requires the fewest changes in character state to produce the characteristics of those tip species. Besides saying what the “best” tree is for a given data set, both methods also provide an ordering of trees, from best to worst. The two methods sometimes disagree about this ordering—most vividly, when they disagree about which tree is best supported by the evidence. For this reason, biologists have had to address this methodological dispute head on, rather than setting it aside as a merely “philosophical” dispute of dubious relevance to scientists “in the trenches.” The main objection that has been made against ML is that it requires the adoption of a model of the evolutionary process that one has scant reason to think is true. ML requires a process model because hypotheses that specify a tree topology (and nothing more) do not, by themselves, confer probabilities on the observations. The situation here is familiar to philosophers as an instance of “Duhem’s Thesis.” Pierre Duhem was a French philosopher of science who contended that physical theories do not entail1 claims about observations unless they are supplemented with auxiliary assumptions (Duhem, 1914). The American philosopher W.V. Quine (1953) later generalized Duhem’s thesis, claiming that all hypotheses fail to entail observational predictions all by themselves. The present point about genealogical hypotheses gives