In Article <6a575g$gpa at net.bio.net>, Joe Staton <jstaton at oeb.harvard.edu> wrote:
>>In article <6a30e6$ro7 at net.bio.net> "Guy A. Hoelzer" <hoelzer at med.unr.edu>
>> >This seems to me to be an overly optimistic view of the value of maximum
>> >likelihood approaches. In general, maximum likelihood is vulnerable to
>> >errors in the chosen model of evolution and in the parameter estimates
>> >that are used.
>>>>Agreed. But on the other hand: a phylogenetic inference method that is
>>/not/ sensitive to the chosen model of evolution would be...?
>Hoelzer's point was not the sensitivity of the evolutionary model in
>general, but the specific model that a maximum likelihood method uses to
>calculate the tree to begin with. If the model of molecular evolution is
>wrong or the parameters needed for the model are poorly estimated, it's a
>case of garbage in yields garbage out (albeit powerfully calculated
>>The model of evolution is another consideration, altogether (i.e.,
>parsimony) which MAY be more robust to giving information about
>evolutionary patterns even if not completely correct. (no flames please)
To add some data to this discussion, you might want to take a look at Mol.
Biol. Evol. 14(1):105-108 (1997). "How often do wrong models produce better
It seems that the maximum likelihood approach is not as sensitive to changes
in the model as one might guess, a priori. Taking that in conjunction with
the problem that the assumptions of the maximum parsimony approach often go
unexamined, I don't think that the rejction of either approach is warranted
given the current state of knowledge.
If you get different results with the two approaches, that should lead
you to examine why that has happened. On the other hand, if you get the
same results with the two approaches, does that necessarily meant that your
confidence in the estimated tree should increase?
Department of Biological Sciences
University of Alberta
Edmonton, Alberta T6G 2E9
wgallin at gpu.srv.ualberta.ca