Text 419, 167 rader
Skriven 2004-10-20 16:29:00 av Michael Ragland (1:278/230)
Ärende: Re: Can You Please Help M
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Guy:

Going to college and becoming a biologist has its advatages. Obviously
you can provide a wealth more on long branch attraction and other
methodological biases than I ever could. Supernerd girl could have found
similar info on the questions she asked using Google. I merely provided
the briefest of answers. You write, "Use of computer simulations in this
regard should be treated cautiously. It is very difficult to avoid
assuming some (if not all) of the same aspects of the evolutionary
process in the generation of the data and in the likelihood model
assumed in the analysis. This results in a circularity that can easily
mislead inferences in favor of the maximum likelihood method. There is
no question that ML can be misled by LBA, like any other topology
estimation method constrained to yield pictures of bifurcating trees if
the assumed evolutionary model is incorrect, which is ALWAYS true in
practice." Am I to take it from this last statement you consider using
computer simulation to generate sequence data for protein families, and
studying the influence of among site rate variation on the performance
of phylogenetic reconstruction as useless?
It states, "Three different tree topologies were used to explore the
effect of long branch attraction with data that incorporated
substitution bias and different degrees of among site rate variation."
Does the "substitution bias" constitute assuming some (if not all) of
the same aspects of the evolutionary process in the generation of the
data and in the likelihood model assumed in the analysis?

Michael Ragland 

BTW If memory serves me correct you read some of my posts and inferred
from them (incorrectly) I think that genetic engineering would lead to
MONSTERS. Certainly I have ethical concerns but I'm not against genetic
engineering of plants or animals although I have posted articles by
authors who are opposed because they have made some valid points. You
told me you would send me a paper you wrote on how artificial novel
genetic changes did not cause major perturbations to the
genome/organism. Instead I received a paper on Self-Organization of
Sytems and you weren't one of the authors and I saw no reference to
novel genetic changes in the document. I felt I was being treated like a
dummie so I posted a very flippant and poor response to the article on
Self Organization of Systems. Perhaps your views on self-organization
mitigate against genetic changes (including novel genetic changes)
having any potentially disfiguring, adverse or major changes on the
genome as a result of genetic engineering. With respect to humans you
may be right if such research is done cautiously, incrementally and
ethically. 

Although not genetic engineering you saw what happenned to that one
young man who received gene therapy and died as a result. And genetic
engineering done with certain "knockout" mice such as the males with NO
resulted in CURIOUS MONSTROSITIES. This was a form of genetic
engineering wasn't it? Removing the enzyme which produces nitric oxide.

I don't think self-organization by itself is an adequate buffer,
cushion, facilitator, etc. against potentially adverse and major
(depending on how one defines major) genetic changes to the genome. My
very basic understanding of a self organized system is an open system
which is NOT GUIDED OR MANAGED FROM THE OUTSIDE. I know you're big on
applying physical principles to everything but I found the following on
WordIQ..yes you're welcome to expand as you did with my responses to
supernerd girl.

It states regarding self-organization in biology:

formation of lipid bilayer membranes,
homeostasis (the self-maintaining nature of systems from the cell to the
whole organism)
morphogenesis, or how the living organism develops and grows. See also
embryology.
the creation of structures by social animals, such as social insects
(bees, ants, termites), and many mammals# flocking behaviour (such as
the formation of flocks by birds, schools of fish, etc.)

The origin of life itself from self-organizing chemical systems, in the
theories of hypercycles and autocatalytic networks.

Surely you see the possibility of genetic engineering of humans one day
modifying characteristics of our self-organization? Who is to say the
self-maintaining nature of systems from the cell to the whole organism,
or how the living organism develops and grows couldn't be theoretically
effected by genetic engineering? Who is to to say the human social
behaviors  (crowds, military formation, subordinance- dominance
hiarchies couldn't be theoretically effected by genetic engineering?

I don't know exactly what that means to state self-organized systems
can't be guided or managed from the outside but if genetic engineers are
externally manipulating the genome that represents to me being guided
and managed from the outside.
 
Michael Ragland 



in article ckjj1b$snf$1@darwin.ediacara.org, Michael Ragland at
ragland66@webtv.net wrote on 10/13/04 8:53 AM: 
"What is 'long-branch attarction' and how susceptible are the 3 major
methods of phylogenetic reconstruction to it?" Thanks a bundle to anyone
who can help. 
---SuperNerdGirl 

Cladistic parsimony(or maximum parsimony) is a method of phylogenetic
inference in the construction of cladograms. Cladograms are branching
tree like structures used to represent lines of descent based on one or
more evolutionary change(s). Cladistic parsimony is used to support the
hypothesis(es) that require the fewest evolutionary changes. It should
be noted that for some types tree, it will consistantly produce the
wrong results regardless of how much data is collected(This is called
long-branch attraction). 

This is true of long-branch attraction (LBA), but it doesn't really
distinguish it from other sorts of methodological biases. Here is a
little more about it. Branch length indicates the amount of independent
evolution that has caused the taxa at the ends of those branches to
diverge from the rest of the taxa included in the analysis. When the
extent of divergence has become too large, the data for the taxa on the
end of the branch effectively becomes randomized relative to the data
for the other taxa, so it becomes less clear how the long-branch taxon
fits into the hierarchical pattern revealed for the rest of the taxa. If
you have only one taxon on a relatively long branch, it will not be very
clear where it should fit into the tree. If you have 2 taxa on
relatively long branches, neither will fit well with the rest. No matter
which method of tree topology estimation you are using (assuming you are
using one that is limited to extracting a hierarchical tree topology),
the 2 taxa appearing to have random data (data that doesn't fit with the
hierarchical pattern present for the other taxa in the analysis) will
tend to be joined as a clade because a pair of random taxa will appear
to share features relative to the set of taxa showing hierarchical
character-state (or distance) distributions. 

Using computer simulation to generate sequence data for protein
families, we studied the influence of among site rate variation on the
performance of phylogenetic reconstruction. The following methods for
phylogenetic reconstruction were compared: maximum likelihood,
parsimony, and distance-matrix analyses. Three different tree topologies
were used to explore the effect of long branch attraction with data that
incorporated substitution bias and different degrees of among site rate
variation. 

While all methods showed errors due to long branch attraction under
extreme conditions, maximum likelihood was by far the most successful in
accurately resolving deep phylogenies 

Use of computer simulations in this regard should be treated cautiously.
It is very difficult to avoid assuming some (if not all) of the same
aspects of the evolutionary process in the generation of the data and in
the likelihood model assumed in the analysis. This results in a
circularity that can easily mislead inferences in favor of the maximum
likelihood method. There is no question that ML can be misled by LBA,
like any other topology estimation method constrained to yield pictures
of bifurcating trees if the assumed evolutionary model is incorrect,
which is ALWAYS true in practice. 

Guy

"It's uncertain whether intelligence has any long term survival value.
Bacteria do quite well with it."

Stephen Hawking
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