mammuthus
Posts: 13
Joined: June 2009
|
More from Sanford. Apparently, MA is the "state of the art" in numerical genetics. Also, he wants to collaborate with y'all. According to Jorge:
| Quote | | The last thing that JS did was ask me for the email address of the people performing these simulations & asking the questions so as to jointly work towards the goal of a more realistic & acceptable-by-all Mendel program. Collaborative science at it best. |
anyway, here is his latest. In italics are the points being responded to (from Steve Schaffner)
| Quote | Dear Colleague - If we can make the program more
realistic, we will. Please explain what you would like
done ... How would you have us model soft selection?
I fail to see why mutations should not cause
extinction, especially given the additive model. As we
approach zero mean fitness, many individuals will
have a fitness of zero or less - we are forced to
truncate them (if you are dead you should not
realistically reproduce), causing population size to
start to rapidly shrink. When there are less than two
individuals, we consider the population extinct.
2) The default value for the maximum beneficial value of mutations is much too low.
Real-world estimates of positive selection coefficients for humans are in the range
of 0.1, not 0.001.
That is easily re-set, but one has to consider if
it is reasonable to realistically build up a genome
by increments of 10% (I am speaking of internal
complexity - not adaptation to an external
environmental factor). I think that is like going
up Mt. Improbable using a helicopter.
3) The starting population is genetically perfect, and all deviations from that state
increase the chance of extinction. This does not accurately model an evolutionary
process, in which no population ever achieves perfection, merely adequacy.
The fact that an ideal organism would have a major competitive advantage
compared to the real one does not imply that the real one is nonfunctional or
doomed to extinction. This is not a model of biological evolution.
We do not assume an ideal starting genotype - we
assume a uniform population after a population
bottleneck - with fitness set arbitrarily at 1.0.
Finally, I also have a technical problem with the program as a software tool.
It does not seem to be possible to run it indefinitely, nor have I seen any cases
where it has even been able to run to equilibrium (or better, steady state).
Whether that is because it continues to track mutations after they fix I don't
know (that's my guess), but it means it is essentially useless as a research tool.
It should be possible to simulate a population of size, say, 20,000 for 200,000
generations. What would the memory requirements for that set of parameters be?
Is the program really able to use the extra memory?
We can turn off individual mutation tracking and just
track the net fitness of each linkage block. We get
nearly indeterminate processing - but we lose lots of
interesting data. I would be happy to cooperate with
you - if you are interested. As far as I can determine,
Mendel is now the "state of the art" in genetic
numerical simulation, and it improves every
month. Are you aware of a better research platform?
Best wishes - John Sanford |
http://www.theologyweb.com/campus....unt=161
For full context, here is the material Sanford is responding too:
| Quote | I haven't raised any claims of fraud, nor am I clamoring for an immediate response. I have the following problems with model, based on what I've seen here.
1) There does not seem to be an option for true soft selection. Even if deleterious alleles do not affect fertility, they still cause the population to become extinct. This is not an accurate model of real genetics.
2) The default value for the maximum beneficial value of mutations is much too low. Real-world estimates of positive selection coefficients for humans are in the range of 0.1, not 0.001.
3) The starting population is genetically perfect, and all deviations from that state increase the chance of extinction. This does not accurately model an evolutionary process, in which no population ever achieves perfection, merely adequacy. The fact that an ideal organism would have a major competitive advantage compared to the real one does not imply that the real one is nonfunctional or doomed to extinction. This is not a model of biological evolution.
Finally, I also have a technical problem with the program as a software tool. It does not seem to be possible to run it indefinitely, nor have I seen any cases where it has even been able to run to equilibrium (or better, steady state). Whether that is because it continues to track mutations after they fix I don't know (that's my guess), but it means it is essentially useless as a research tool. It should be possible to simulate a population of size, say, 20,000 for 200,000 generations. What would the memory requirements for that set of parameters be? Is the program really able to use the extra memory?
If Sanford (or co-author) wishes to address these criticisms, I would welcome the response. As it stands, however, I do not see how one can use this model to make any statements about the likely behavior of evolving populations in the real world. |
|
