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Author
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Topic: Scale invariance, irreducible complexity and robustness
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Frances
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Member # 169
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posted 27. October 2002 23:53
In an effort to revive the excellent exchanges between Dembski and Deanne in this thread I have been collecting some references to research that seem applicable here.
First of all the PhD thesis of Richard Watson Compositional Evolution: Interdisciplinary Investigations in Evolvability, Modularity, and Symbiosis.
seems of particular interest. Richard addresses Behe's claims of IC and shows how compositional evolution could explain ICnessn while accretive mechanisms might have a much harder time
quote:
We use the term ‘compositional’ to refer to variation mechanisms that combine together systems or subsystems of genetic material, or feature complexes, that have been semi-independently preadapted in parallel in different lineages.
Examples in nature include: Normal mechanisms of sexual recombination (under particular conditions of population diversity and genetic linkage from the arrangement of genes on the chromosome), and mechanisms of interspecific combination such as horizontal gene transfer; also, mechanisms of ‘symbiotic encapsulation’ such as endosymbiosis or other mechanisms that encapsulate a group of simple entities into a complex entity at a higher level of organisation, as exhibited in several of the major transitions in evolution. · In contrast, we use the term ‘accretive’ to refer to variation mechanisms that accumulate random variations in genetic material or features, i.e. the new genetic material or features that are introduced by such changes have not been pre-adapted elsewhere as a set. Thus accretive evolution is driven predominantly by small modifications, i.e. ‘successive slight modifications’ (Darwin 1859), which forms the basis of our common understanding of evolutionary change.
Examples in nature include: Genetic mutation and sexual recombination in the absence of favourable genetic linkage.
It seems that Richard's model is very similar to the argument of Deanne as far as scale invariance is concerned. The properties of scale-invariance seem to be related to simple properties of incremental construction.
I would also like to tie this in with complexity and robustness
It may very well be that not only are 'indirect routes' hardly that unlikely but the evidence found in nature of scale invariance suggests an incremental mechanism. So gene duplication and further mutation and selection may be one pathway, other pathways include the compositional mechanisms proposed by Watson.
Let me also introduce the following article by Gisiger Scale invariance in biology: coincidence or footprint of a universal mechanism?
A good introduction on scale invariance in networks
quote:
However, possible scale-free features of genetic and signaling networks could reflect the networks’ evolutionary history, dominated by growth and aggregation of different constituents, leading from simple molecules to complex organisms. With the fast advances being made in mapping out genetic networks, answers to these questions might not be too far away.
How do we tie this in with ID? Well, lets assume that TRIZ is a useful paradigm in intelligent design
TRIZ recognizes two distinct mechanisms of invention, 1) trial and error 2) intentional mechanisms.
Can we based on TRIZ determine what the various mechanisms of innovation/invention predict and determine if we can find supporting evidence in biology?
I believe that the findings of scale invariance point stronger to mechanism 1) than to mechanism 2). Rather than add to an existing network of hubs and nodes 2) invites one to break the nodes and reroute them, to basically reengineer the problem.
Bracht seems quite clear on the concepts
quote:
However, there are other changes that require a fundamental re-engineering of the biological hypervolume, and which cannot, in any case, be considered mere variants upon previously existing systems.
Which suggests that rather than tinkering, mechanism 2) is a re-engineering, not a variation on previously existing systems. This seems to be at odds with the scale invariance found in nature.
What is indeed fascinating is for instance the Cambrian explosion
quote:
The lack of experimentally observed heritable changes in body plan coupled with the suddenness of the origin of phyla in the Cambrian explosion suggests that a new mechanism is needed to account for the data.
Seems that a few well placed and conserved hubs and some variation may be all that was needed (Hox Genes).
One could of course argue that an intelligent designer were but a tinkerer using 1) to improve upon previous designs but what would make such an ad hoc explanation better than what we have so far?
Dembski seems to be equally clear in his predictions
quote:
Darwinian evolution is a trial-and-error method for gradually improving preexisting functions and for co-opting serendipitous functions. Within Darwinian evolution natural selection supplies the trial and random variation the error. Although trial and error plays a role in technological evolution, trial and error is too myopic to serve as the powering force behind technological evolution.
Combine this with what biology teaches us and one may wonder if the conclusion Biology confirms the patterns of technological evolution outlined by TRIZ. Significantly, these patterns are non-Darwinian. are supportable and even if they were non-Darwinian, they need not be considered evidence for ID. In the end the argument seems to center around the claims wrt CSI. 1) CSI cannot arise through natural causes 2) nature contains CSI. Both premises while required for a design inference are not that self evident.
I have attempted to use TRIZ as a model/theory for how ID expects innovation/change to occur and compared it against the findings in nature. Can TRIZ, especially mechanism 2) explain the scale invariance found abundantly in nature? It seems evolutionary mechanisms surely can.
[ 28. October 2002, 17:19: Message edited by: Frances ]
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Mike Gene
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Member # 149
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posted 10. November 2002 21:44
There is also a couple of good reads in the Oct 25 Science . Here are some interesting excerpts from "Network Motifs: Simple Building Blocks of Complex Networks":
quote:
We applied the algorithm to several networks from biochemistry (transcriptional gene regulation), ecology (food webs), neurobiology (neuron connectivity), and engineering (electronic circuits, World Wide Web).
We analyzed the two best characterized transcriptional regulation networks, corresponding to organisms from different kingdoms: a eukaryote (the yeast Saccharomyces cerevisiae) and a bacterium (Escherichia coli) . The two transcription networks show the same motifs: a three-node motif termed "feedforward loop" and a four-node motif termed "bi-fan." These motifs appear numerous times in each network, in nonhomologous gene systems that perform diverse biological functions. The number of times they appear is more than 10 standard deviations greater than their mean number of appearances in randomized networks.
We next studied the neuronal connectivity network of the nematode Caenorhabditis elegans.....
Two of these motifs (feedforward loop and bi-fan) were also found in the transcriptional gene regulation networks. This similarity in motifs may point to a fundamental similarity in the design constraints of the two types of networks. Both networks function to carry information from sensory components (sensory neurons/transcription factors regulated by biochemical signals) to effectors (motor neurons/structural genes). The feedforward loop motif common to both types of networks may play a functional role in information processing.
We also studied several technological networks. We analyzed the ISCAS89 benchmark set of sequential logic electronic circuits..... The forward logic chips share the feedforward loop, bi-fan, and bi-parallel motifs, which are similar to the motifs found in the genetic and neuronal information-processing networks.
None of the network motifs shared by the food webs matched the motifs found in the gene regulation networks or the World Wide Web. Only one of the food web consensus motifs also appeared in the neuronal network. Different motif sets were found in electronic circuits with different functions. This suggests that motifs can define broad classes of networks, each with specific types of elementary structures. The motifs reflect the underlying processes that generated each type of network; for example, food webs evolve to allow a flow of energy from the bottom to the top of food chains, whereas gene regulation and neuron networks evolve to process information. Information processing seems to give rise to significantly different structures than does energy flow. -emphasis added
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RBH
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Member # 380
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posted 10. November 2002 22:32
From Mike Gene's reference: quote:
None of the network motifs shared by the food webs matched the motifs found in the gene regulation networks or the World Wide Web. Only one of the food web consensus motifs also appeared in the neuronal network. Different motif sets were found in electronic circuits with different functions. This suggests that motifs can define broad classes of networks, each with specific types of elementary structures. The motifs reflect the underlying processes that generated each type of network; for example, food webs evolve to allow a flow of energy from the bottom to the top of food chains, whereas gene regulation and neuron networks evolve to process information. Information processing seems to give rise to significantly different structures than does energy flow. -emphasis added
Dare I mention MDT design themes in this context? ![[Wink]](wink.gif)
RBH
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Mike Gene
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Member # 149
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posted 11. November 2002 06:49
RBH: Dare I mention MDT design themes in this context?
Sure, a possible mosaic of the blind and intelligent watchmakers at work? Aren't you bothered by the fact that your MDT doesn't incorporate RM&NS?
Actually, I think it would be more interesting if you applied MDT to my thread, "Error Correction Runs Deep." Seems like an obvious opening for ya.
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