bernard Wrote:
-------------------------------------------------------
> Note: this is for the lurkers. WG can just ignore
> it.
>
> On a couple of threads, Intelligent Design has
> been bandied about, but has not been discussed or
> described thoroughly. I have been reading up on it
> and I would like to do a brief piece with some
> references for further reading—
>
> First, a quote from Richard Dawkins (2004: 549)
> describing the basic philosophy of Intelligent
> Design— “This is the ancient ‘Argument from
> Design,’ also called ‘Argument from Paley’s
> Watchmaker,’ or the ‘Argument from Irreducible
> Complexity.’ I have less kindly called it the
> ‘Argument from Personal Incredulity’ because it
> always has the form: ‘I personally cannot imagine
> a natural sequence of events whereby X could have
> come about. Therefore it must have come about by
> supernatural means.’ Time and again scientists
> have retorted that if you make this argument, it
> says less about nature than about the poverty of
> your imagination. The ‘Argument from Personal
> Incredulity’ would lead us to invoke the
> supernatural every time we see a god conjuror
> whose tricks we cannot fathom.”
>
> There are number of proponents if ID, but the key
> figures are Michael Behe and William Dembski. Both
> of them accept the current age of the earth and
> will argue that ID is compatible with common
> descent. “The central issue, therefore, is not the
> relatedness of organisms, or what is typically is
> called common descent. Rather, the central issue
> is how biological complexity emerged and whether
> intelligence played an indispensable (which is not
> to say exclusive) role in its emergence.”
> (Dembski, 2004: 323). Therefore, young earth
> creationists, like William Morris, are critical of
> ID.
> Ruse (2003: 315-16) gives a succinct description
> of Behe’s key concept: “The biochemist Michael
> Behe, in his best-selling book Darwin’s Black
> Book, most fully articulated the empirical case.
> He focused on “irreducible complexity,” which he
> defined as “a single system composed of several
> well-matched, interacting parts that contribute to
> the basic function, wherein the removal of any one
> of these parts causes the system to effectively
> cease functioning” (p. 39). Behe added that any
> “irreducibly complex biological system, if there
> is such a thing, would be a powerful challenge to
> Darwinian evolution. Since natural selection can
> only choose systems that are already working, then
> if a biological system cannot be produced
> gradually it would have to arise as an integrated
> unit, in one fell swoop, for natural selection to
> have anything to act on” (p. 39). Behe’s examples
> of irreducible complexity are cited over and over
> by other proponents. He proposes that a 5-part
> mousetrap is a good model because if any part is
> removed it will no longer work as a mousetrap.
> Behe’s most cited biological examples are: 1) the
> bacterial motion using a flagellum which is driven
> by a kind of rotary motor and which has a number
> of parts including several ring structures in the
> base and 2) the cascade of biochemical reactions,
> which are sequentially involved in human blood
> clotting.
>
> I. I’ll deal with each of these in turn. Prof.
> John McDonald of the University of Delaware has
> posted drawings on a web site that show how a
> mousetrap may be constructed with just three, two,
> or even just one part. McDonald's mousetrap plans
> are available at: . Further Behe (2004: 320-21)
> states:
> “Rather more significant though, is that Behe’s
> mousetrap shows a misunderstanding of the way
> natural selection works. No Darwinian would deny
> that in organisms there are parts which, if
> removed, would lead at once to malfunctioning or
> nonfunctioning of the systems in which they occur.
> The point is not whether the parts now in place
> could be removed without collapse but whether they
> could have been put in place by natural selection.
>
> To counter Behe’s artifactual analogy we can think
> of other artifactual analogies that show precisely
> how the apparently impossible could be achieved.
> Consider an arched bridge made from cut stone,
> without cement, held in place only by the force of
> the stones one against another. If you tried to
> build the bridge from scratch, upward and then
> inward, you would fail—the stones would keep
> falling to the ground. Indeed the whole bridge now
> would collapse if you were to remove the keystone
> or any stone surrounding it. What you must do to
> construct an arch is, first, build a supporting
> structure (possibly an earthen embankment) on
> which you lay the stones of the bridge, until they
> are all in place. Then you remove the structure,
> which is no longer needed and in fact is in the
> way of walking under the bridge. Likewise, one can
> imagine a biochemical sequential process with
> several stages, on parts of which other processes
> piggyback, as it were. When the here to
> nonsequential parasitic processes link up and
> start functioning independently, the original
> sequence is eventually removed by natural
> selection because it is redundant or drains
> resources.
> Moving from the pretend to the actual, today’s
> Darwinians have many examples of the most complex
> of processes that have been put in place by
> selection. Take as an example the process whereby
> energy from food is converted into a form that can
> be used by the cells. This process, called the
> Krebs cycle, occurs in the cell’s mitochondria and
> centers on two molecules, ATP (adenosine
> triphosphate) and ADP (adenosine diphosphate). The
> former is more energy-rich than the latter and is
> degraded by the body when it needs power. Not only
> are the molecules themselves complex but so also
> is the Krebs cycle that makes ATP from other
> sources of energy. There are almost a dozen
> sub-processes in the cycle, each making a new
> product from an earlier one. Every one of these
> sub-processes demands its own enzyme (these are
> molecular substances that prior chemical
> reactions). Do not think that the cycle appeared
> out of thin air, complete and entire as it were.
> Each part of the cycle started life doing
> something else and then (in true Heath Robinson
> fashion) was grabbed by the cells and put to a new
> use. Although, when they set out, the scientists
> who found all of this out certainly did not have
> Behe and his “irreducible complexity” in mind, one
> could imagine that they did, especially from the
> way they set up the problem. “The Krebs cycle has
> been frequently quoted as a key problem in the
> evolution of living cells, hard to explain by
> Darwin’s natural selection: How could natural
> selection explain the building of a complicated
> structure in toto, when the intermediate stages
> have no obvious fitness functionality?”
> (Meléndez-Hervia et al. 1996:302). A Behe-type
> problem but no Behe-type answer. To the contrary,
> the various parts of the Krebs cycle had their
> original uses, and then these were taken over for
> the whole.
>
> Further, as Dawkins (2004:550-552 )points out:
> “Kenneth Miller of Brown University deals with the
> whole question in a tour de force of cleat
> exposition. As Miller shows, the allegation that
> the component parts of the flagellar motor have no
> other functions is simply false. As one example,
> many parasitic bacteria have a mechanism for
> injecting chemicals into host cells called the
> TTSS (Type Three Secretory Apparatus). The TTSS
> makes use of a subset of the very same proteins
> that are used in the flagellar motor. In this case
> they are used not for providing rotatory motion of
> a circular hub, but for making a circular hole in
> a host’s cell wall. Miller summarizes:
> Stated directly, the TTSS does its dirty work
> using a handful of proteins from the base of the
> flagellum. From the evolutionary point of view,
> this relationship is hardly surprising. In fact,
> it’s to be expected that the opportunism of
> evolutionary processes would mix and match
> proteins to produce new and novel functions.
> According to the doctrine of irreducible
> complexity, however, this should not be possible.
> If the flagellum is indeed irreducibly complex,
> then removing just one part, let alone 10 or 15,
> should render what remains ‘by definition
> nonfunctional.’ Yet the TTSS is indeed fully
> functional, even though it is missing most of the
> parts of the flagellum. The TTSS may be bad news
> for us, but for the bacteria that possess it, it
> is a truly valuable biochemical machine. The
> existence of TTSS in a wide variety of bacteria
> demonstrates that a small portion of the
> ‘irreducibly complex’ flagellum can indeed carry
> out an important biological function. Since such a
> function is clearly favored by natural selection,
> the contention that the flagellum must be fully
> assembled before any of its component parts can be
> useful is obviously incorrect. What this means is
> that the argument for intelligent design of the
> flagellum has failed.”
>
> And, finally Ruse (2003: 321-322) points out:
> “Behe’s position does not seem plausible, given
> what we know of the nature of mutation and
> stability of biological systems over time. When
> exactly does the Intelligent Designer supposedly
> strike to do its work? In Darwin’s Black Box Behe
> suggests that everything might have been done long
> ago and then left to its own devices. “The
> irreducibly complex biochemical systems that I
> have discusses.. . did not have to be produced
> recently. It is entirely possible, based simply on
> an examination of the systems themselves, that
> they were designed billions of years ago and that
> they could have been passed down to the present by
> the normal processes of cellular reproduction (pp.
> 227-228). Although Behe ignores the history of the
> preformed genes from this point between their
> origin (when they would not have been needed) and
> today (when they are in full use), we should not.
> According to the biochemist Kenneth Miller
> (1999:162-163), “As any student of biology will
> tell you, because these genes are not expressed,
> natural selection would not be able to weed out
> genetic mistakes. Mutations would accumulate in
> these genes at breathtaking rates, rendering them
> hopelessly changed and inoperable hundreds of
> millions of years before Behe says that they will
> be needed.” There is a mass of experimental
> evidence showing this to be the case. Behe’s idea
> of a designer doing everything back then and
> leaving matters to their natural fate is “pure and
> simple fantasy.”
>
> II. blood clotting. This will be shorter. Behe’s
> claim is easily dealt with. As Ian Musgrave (2005)
> states : ”Miller has pointed out to Behe that
> whales and dolphins lack the contact pathway
> (Factor XII or Hageman Factor) (5). Furthermore,
> puffer fish don’t have the pathway either (3). So
> two groups of vertebrates can live happily without
> a major arm of the clotting cascade. Behe has not
> addressed this.” The evolution of the clotting
> cascade is detailed in Miller (n.d). Musgrave also
> describes experiments with knockout mice that show
> that clotting can proceed when mice with different
> parts of the cascade genetically eliminated are
> interbred and compensate for the missing parts of
> the clotting cascade. As described above, the
> evolution of a much more complex biochemical
> system, the Krebs cycle, has been described
> arising from the putting together of simpler
> components that originally had different
> functions.
> %%%%%
> William Dembski
>
> William Dembski is the theoretician of the
> movement. His books are full of abstruse and
> complicated mathematical formulas. He claims to be
> using information theory to derive his
> conclusions. His basic claim is that “complex
> specified information (CSI)” cannot be generated
> by natural selection and therefore must be due to
> an “intelligence.” In his interesting review of
> Dembski (2002), Orr (2002) puts it this way: “An
> object, event, or structure exhibits specified
> complexity if it is both complex (i.e., one of
> many live possibilities) and specified (i.e.,
> displays an independently given pattern). A long
> sequence of randomly strewn Scrabble pieces is
> complex without being specified. A short sequence
> spelling the word "the" is specified without being
> complex. A sequence corresponding to a
> Shakespearean sonnet is both complex and
> specified.” Dembski has designed a “filter” which
> eliminates the possibility that a piece of
> information is due to chance or following a law
> and thus is truly “complex specified information.”
> He also calculates the possibility of the elements
> coming together simultaneously and sets a lower
> limit of 10^150 to assert that something is due to
> design. Dembski’s prime “real-life” example is
> Behe’s bacterial flagellum.
>
> Mark Perakh (2004: 27), who works on statistical
> physics and is thus qualified to cut through the
> smog, has this to say about Dembski’s use of
> mathematical formulations: “Actually, The Design
> Inference contains little of genuine mathematics,
> but is full of mathematism, that is, the use of
> mathematical symbolism as embellishment, often
> only to create an impression of a scientific rigor
> of the discourse. And again (2004:38)”Actually all
> these convoluted notions of detachability,
> tractability, and delimitation seem superfluous
> and the criterion of specification seems to boil
> own to the simple requirement that can be
> expressed as: an event is specified if it displays
> a recognizable pattern. Of course, if Dembski
> limited his discourse to such a brief and easily
> comprehensible assertion he would not be able to
> write a whole book with its seemingly
> sophisticated mathematical apparatus. What does
> recognizability entail? To recognize a pattern we
> must have in mind some image, independent of the
> pattern actually observed, to which we compare the
> observed pattern. That is actually the idea of
> “detachability,” stripped of its sophisticated
> embellishments.. .”
>
> What really drove the point home to me was
> Perakh’s description of the various information
> theories that Dembski claims to be using. The
> seminal papers are by Shannon (1948). Perakh
> 92004: 64-67)” In fact, what information theory
> studies is the communication process, viewed as
> the transmission of information, regardless of the
> presence or absence of a meaningful message in
> that information.. . Information has no relation
> either to the semantic contents of the message or
> to the particular appearance of the symbols used
> to record it. It is essential for our discussion
> to note that the more random the transmitted text,
> the larger the amount of information it carries..
> . One of the measures of information according to
> information theory, is a quantity named entropy.
> To all intents and purposes, it behaves like its
> namesake in thermodynamics. The entropy of a text
> quantitatively characterizes the level of disorder
> in that text. The total entropy of a text as a
> whole is proportional to the text’s length and is
> therefore an extensive quantity. A more
> interesting quantity is the specific entropy,
> which is the entropy of a unit of text, and
> therefore is an intensive quantity. Usually it is
> expressed in as entropy per character and measured
> in bits per character. In the following
> discussion, unless indicated otherwise, the term
> entropy will mean the specific entropy. There
> exists a hierarchy of texts in regard to their
> entropy For example, consider a string of the same
> letter (like A) repeated, say, a million times:
> AAAAAAA.. .etc. This meaningless text is perfectly
> ordered. The entropy of the text is practically
> zero. Now consider a text obtained , for example,
> by what we cal the urn technique .. . Let a text
> in an “urn language” be, say, a million letters
> long. This string is almost always gibberish
> (there is some, extremely small probability that a
> string of an urn language happens to be a piece of
> a meaningful message). If, as is overwhelmingly
> the case, this string is gibberish, in an
> overwhelming majority of situations there is no or
> very little order in that string. We call it a
> random string. The entropy of that meaningless
> random string is large, and so is the information
> carried by that string. Meaningful texts are
> located somewhere in the middle of the entropy
> scale, their entropy being much larger than in
> perfectly ordered texts of very low entropy (like
> AAAAA. ..) but much smaller than in the
> meaningless random texts. Here are some typical
> numbers. The entropy of a normal meaningful text
> in English (as was estimated already by Shannon)
> is about 1 bit per character. On the other hand,
> the entropy of a text written in urn language,
> that is the entropy of a randomized sequence of 27
> symbols (26 letters plus space), may be as high as
> 4.76 bits per character.”
> Perakh (2004: 67) concludes “Reading Dembski’s
> treatment of information, including his alleged
> law, leaves the impression that when discussing
> CSI he does not notice how inconsistently he
> switches back and forth between the concepts of
> information in the sense of information theory and
> complex specified information (which actually
> means a meaningful message and hence is not
> information in the sense of information theory).
> The mathematical apparatus of information theory,
> which Dembski uses in The Design Inference, is not
> applicable to meaningful messages, i.e., to what
> he refers to as CSI. In my view this makes
> Dembski’s entire treatment of information largely
> off the mark.”
>
> The next point to consider is Dembski’s arguments
> of extreme unlikeliness of complex events. This is
> just a different version of the creationist
> calculations of the improbability of a hurricane
> assembling a B-52 bomber. As mentioned above, no
> Darwinian has ever argued that organisms came
> together in a single event. Ruse (2003: 325-27)
> writes: “Natural processes producing adaptation is
> about as likely as a monkey randomly typing a play
> by Shakespeare, these antievolutionists have
> claimed. Famously, Richard Dawkins has scotched
> this kind of argument. Selection decimates the
> ever-increasing randomness factors. Choosing a
> line from Shakespeare—METHINKS IT IS A
> WEASEL—Dawkins shows that one can set up a
> computer program that produces letters (or blanks)
> randomly in all twenty-eight spaces that this
> sentence occupies. It can produce UMMMK JK CDZZ F
> ZD DSDSKSM, for instance, or S SS FMCV PU I
> DDRGLKDXRRDO. If one were working randomly, the
> chances of producing the target sentence in one
> try is about 1 in 10,000 million, million,
> million, million, million, million against. Just
> impossible in fact. Now rejig the program so that
> it remembers a successful move, in this case
> getting a little closer to the target sentence.
> With this constraint added into a system for
> producing random letters, the target can be
> reached in less than fifty moves. So much for all
> this multiplication. “There is a big difference,
> then, between cumulative selection (in which each
> improvement, however slight, is used as the basis
> for future building), and single-step selection
> (in which each new “try” is a fresh one.” (Dawkins
> 1996:49). The Intelligent design people do not
> give this example much weight, pointing out
> (correctly) that it has many dis-analogies with
> real-life situations, beginning with the fact that
> Dawkins specified the end-point, whereas in nature
> there is supposedly no such fixed goal. Even a
> progressivist like Dawkins is not going to say
> that the Cambrian led inevitably to Englishmen.
> But Dawkins himself conceded this as soon as he
> gave his example. He was not trying to simulate
> nature in every respect. He was simply showing
> that arguments which multiply randomness to a
> point beyond possibility can be countered simply
> by factoring in selection.
>
> Dembski criticizes Dawkins’ example, from Orr’s
> (2002) review:
> “The apparent success of Dawkins's algorithm at
> getting to METHINKS… must therefore be just that,
> an appearance. If Dawkins tried reaching his
> target when averaging over all fitness functions,
> he'd find he does no better than blind search. So
> why does Dawkins's algorithm seem to work? The
> answer is that it subtly cheats: it starts not
> only with a target but also with a fitness
> function that leads straight to it. Everything's
> been cooked into the fitness function. Algorithms
> like Dawkins's thus "fail to generate specified
> complexity because they smuggle it in during
> construction of the fitness function."
>
> Hence Dembski's big claim: "Darwinian mechanisms
> of any kind, whether in nature or in silico, are
> in principle incapable of generating specified
> complexity." At best, Darwinism just shuffles
> around preexisting specified complexity, using up
> that available in the fitness function to give the
> appearance of producing it de novo.
>
> We can now complete the Dembskian Syllogism:
> Organisms show specified complexity; Darwinism
> can't make it; therefore, something else does. You
> won't be surprised to learn that that something
> else is intelligence. Indeed the "great myth of
> contemporary evolutionary biology is that the
> information needed to explain complex biological
> structures can be purchased without
> intelligence."
> Nice answer, wrong question
>
> The problem with all this is so simple that I hate
> to bring it up. But here goes: Darwinism isn't
> trying to reach a prespecified target. Darwinism,
> I regret to report, is sheer cold demographics.
> Darwinism says that my sequence has more kids than
> your sequence and so my sequence gets common and
> yours gets rare. If there's another sequence out
> there that has more kids than mine, it'll displace
> me. But there's no pre-set target in this game.
> (Why would evolution care about a pre-set place?
> Are we to believe that evolution is just
> inordinately fond of ATGGCAGGCAGT…?) Dembski can
> pick a prespecified target, average over all
> fitness functions, and show that no algorithm
> beats blind search until he's blue in the face.
> The calculation is irrelevant. Evolution isn't
> searching for anything and Darwinism is not
> therefore a search algorithm. The bottom line is
> not that the NFL theorems are wrong. They're not.
> The bottom line is that they ask the wrong
> question for what Dembski wants to do. More
> precisely, the proper conclusion isn't that the
> NFL theorems derail Darwinism. The proper
> conclusion is that evolutionary algorithms are
> flawed analogies for Darwinism.
>
> The astonishing thing is that Dembski knows all
> this. In a remarkable revelation—and one that
> follows two hundred pages of technical
> mumbo-jumbo—Dembski suddenly announces that
> Darwinists won't find his NFL objection terribly
> relevant. And why not? For the very reason I just
> gave. Dembski even quotes Richard Dawkins at
> length, who, it turns out, warned all along that
> his METHINKS… example is
>
> …misleading in important ways. One of these is
> that, in each generation of selective "breeding,"
> the mutant "progeny" phrases were judged according
> to the criterion of resemblance to a distant ideal
> target, the phrase METHINKS IT IS LIKE A WEASEL.
> Life isn't like that. Evolution has no long-term
> goal. There is no long-distance target, no final
> perfection to serve as a criterion for selection….
> In real life, the criterion for selection is
> always short-term, either simple survival or, more
> generally, reproductive success (Dawkins 1996:
> 50).
>
> Ruse (2003) 327-328 deals with a remaining
> Dembskian objection— that no new complexity can be
> generated by selective forces:
> “The real question is whether more sophisticated
> computer models can show that selective forces can
> generate genuine complexity—the kind that we
> associate with real adapted organisms— without
> having to put in such complexity into the pool in
> the first place. And the answer is that they can.
> A beautiful example was devised by the biologist
> Thomas S. Ray. Tierra—an artificial world he
> created—lives in Ray’s computer; the “organisms”
> who inhabit it are self-replicating programs of an
> initially fixed length (80 instructions long).
> “Having determined the address of its beginning
> and end, it subtracts the two to calculate its
> size, and allocates a block of memory of this size
> for a daughter cell. It then calls the copy
> procedure which copies the entire genome into the
> daughter-cell memory, one instruction at a time”
> (Ray 1996). Other than being self-replicating,
> these creatures (as we might neutrally call them)
> have no functions built in. They exist in a kind
> of memory pool, and each creature has a chunk of
> this memory. They cannot write into the program of
> other creatures, but they can read the information
> from other creatures and use this information.
> Time is limited for each creature, and when it has
> a block of time, it can use it to self-replicate.
> It then goes to the end of the queue and has to
> wait its turn for more time. There is a process
> (the “reaper”) by which the creatures get
> eliminated, but creatures can put off extinction
> by performing tasks (like reproduction) more
> efficiently than their fellows. Mutations are
> introduced into the mix by making the information
> of the creatures, and their replication, subject
> to random changes.
>
> What happens when you set things in motion (Ray
> 1996: 124)?
> “Once the soup is full, individuals are initially
> short-lived, generally reproducing only once
> before dying; thus, individuals turn over very
> rapidly. More slowly, there appear new genotypes
> of size 80, and then new size classes. There are
> changes in the genetic composition of each size
> class, as new mutants appear, some of which
> increase significantly in frequency, sometimes
> replacing the original genotype. The size classes
> which dominate the community also change through
> time, as new size classes appear.. . some of which
> competitively exclude sizes present earlier. Once
> the community becomes diverse, there is a greater
> variation in the longevity and fecundity of the
> individuals.
> In addition to the raw diversity of genotypes and
> genome sizes, there is an increase in the
> ecological diversity. Obligate commensurable
> parasites evolve, which are not capable of
> self-replication in isolated culture, but which
> can replicate when cultured with normal
> (self-replicating) creatures. These parasites
> execute some part of the code of their hosts, but
> cause them no direct harm, except as competitors.
> Some potential hosts have evolved immunity to the
> parasites, and some parasites have evolved to
> circumvent this immunity.”
>
> If there were a designer, he/she/it had to be
> extremely sloppy and inefficient because less than
> 5% of the human genome codes for genes. Miller
> (1994) points out that: “ In fact, the human
> genome is littered with pseudogenes. Gene
> fragments, “orphaned” genes, “junk” DNA, and so
> many repeated copies of pointless DNA sequences
> that it cannot be attributed to anything that
> resembles intelligent design. If the DNA of a
> human being or any other organism resembled a
> carefully constructed computer program with neatly
> arranged and logically structured modules, each
> written to fulfill a specific function, the
> evidence of intelligent design would be
> overwhelming. In fact, the genome resembles
> nothing so much as a hodgepodge of borrowed,
> copied, mutated, and discarded sequences and
> commands that has been cobbled together by
> millions of years of trial and error against the
> relentless test of survival. It works, and it
> works brilliantly; not because of intelligent
> design, but because of the great blind power of
> natural selection to innovate, test, and to
> discard what fails in favor of what succeeds. The
> organisms that remain alive today, ourselves
> included, are evolution’s great successes.”
> %%%%%
> There are a number of philosophical and logical
> problems associated with ID which I won’t discuss.
> ID articles have not been published in per
> reviewed journals in the relevant disciplines. In
> almost ten years, ID has not developed any further
> examples or “irreducible complexity” than the
> flagellum and the clotting cascade—not a very good
> testimony to its productivity as a research
> strategy. In a Kuhnian sense, any theory seeking
> to replace another has to be able to explain
> everything than the previous theory has explained
> plus be able to explain areas that the theory it
> seeks to replace has not. Even posing the
> question, makes the position of ID versus the
> modern synthetic theory of evolution laughable.
>
>
>
>
>
> Behe, M. 1996. Darwin’s Black Box: the Biochemical
> challenge to Evolution. New York: Free Press.
>
> Dawkins, R. 1996. The Blind Watchmaker New York:
> Norton.
>
> Dawkins, R. 2004. The Ancestor’s Tale New York:
> Houghton Mifflin
>
> Dembski, Wm. 2002. No Free Lunch: Why Specified
> Complexity Cannot Be Purchased without
> Intelligence. New York: Rowman & Littlefield
>
> Dembski, Wm. 2004. “The Logical Underpinnings of
> Intelligent Design,” in Wm. A. Dembski and M.
> Ruse, eds.Debating Design. From Darwin to DNA, pp.
> 311-329 Cambridge: Cambridge Univ. Press.
>
> Meléndez-Hevia, E. et al. 1996. “The Puzzle of the
> Krebs Citric Acid Cycle: Assembling the Pieces of
> Chemically Feasible Reactions, and Opportunism in
> the Design of Metabolic Pathways During
> Evolution,” Journal of Molecular Evolution 43:
> 293-303.
>
> Miller, K.R. n.d. “The evolution of the clotting
> system”
> (http://)biocrs.biomed.brown.edu/Darwin/DI/clot/Cl
> otting.html
>
> Miller, K. R. 1994. “Life’s Grand Design,”
> Technology Review 97 (#2):28-29.
>
>
> Miller, K.R. 1999. Finding Darwin’s God. New York:
> Harper and Row
>
> Miller, K.R. 2004. “The flagellum unspun: the
> collapse of ‘irreducible complexity,” in Wm. A.
> Dembski and M. Ruse, eds.Debating Design. From
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> Other resources


Thank you, Bernard. Well done!