Letter to Trends in Microbiology
4:41 PM PDT, May 21, 2009
Dear Readers, The January 2009 issue of Trends in Microbiology contains an article entitled “Bacterial flagellar diversity and evolution: seek simplicity and distrust it?” Unfortunately, like many people, the authors have a mistaken view of irreducible complexity, as well as a very shallow idea of what a Darwinian “precursor” to an irreducibly complex system might be. I wrote a letter to the editor of the journal to point out these difficulties. Alas, they said they had no room to publish it. Below is the letter that I sent.
Letter to Science
9:57 AM PDT, May 21, 2009
Dear Readers, The May 1st issue of Science contains a “News Focus” article entitled “On the Origin of the Immune System.” While describing some current work in the area the author, John Travis, makes liberal use of myself as an unreasonably-skeptical foil. I wrote a letter to the editor of Science pointing out inaccuracies in the story but, gee whiz, they didn’t think the letter would be of sufficient interest to their readers to print it. Below I reproduce the unpublished letter for those who might be interested in my reaction to the article.
“The Old Enigma,” Part 3 of 3
8:14 AM PDT, April 2, 2009
Dear Readers, This post continues directly from Part 2. Second, the authors assume that, in the absence of phenotypic mutations, the first genotypic mutation would be strictly neutral. That is, the selection coefficient for the first mutation is very, very close to zero. It turns out that this is a critical feature. If the first mutation were slightly positive itself (without considering look-ahead) then it could be selected on its own, and the look-ahead effect makes little difference. On the other hand, if the first mutation is slightly negative (including look-ahead), then it will not be positively selected and, again, the effect makes essentially no difference. It is only in a very restricted range of selection coefficients that any significant influence will be seen. A related point is the question: except for purposes of illustration, why should the look-ahead effect be conceptually separated from everything else that goes into the selection coefficient? Clearly any mutation can have many effects, from stabilizing (or destabilizing) the structure of a protein to increasing (or de-) its interaction with other proteins, to favorably (or un-) affecting the energy budget of a cell, and so on. All of the effects can influence whether the mutation is favorable overall or not, so why separate out look-ahead? If, considering all influences, a particular mutation is favorable because offspring with the mutation survive with higher probability, then that is represented by a positive selection coefficient; if unfavorable, a negative coefficient. It is dubious to subdivide survival due to a particular mutation into tiny parts. Third, the look-ahead effect is manifestly a double-edged sword. Consider the sequence of the protein one mutation before it reached what we previously called the “unmutated state” — that is, the sequence of the protein that was fixed in the population right before it reached the sequence that was two mutations from the highly favorable form. We can call it “sequence minus one.” Now suppose a mutation appears in the DNA of one cell that would take us to the starting sequence (call it “sequence zero”) if it spread and became fixed in the population. The next mutation (call it “sequence plus one”) can appear in this individual cell as a phenotypic, look-ahead mutation. The final mutation (“sequence plus two”), which has the highly selectable feature, does not appear even as a phenotypic mutation in this cell. But now suppose that sequence plus one was not strictly neutral without look-ahead, but somewhat deleterious (as most protein mutations are). Then, because of the look-ahead effect, sequence zero will be selected against, and the probability that the population ever develops sequence zero will be much lower. The take-home point is that, although looking ahead might help the final step a bit if the penultimate mutation is otherwise strictly neutral, the look-ahead effect will actively inhibit the development of a multimutation feature if one of the steps in a mutational pathway is somewhat deleterious. And the more deleterious it is, the more effectively the path is blocked. In a rugged adaptive landscape, the look-ahead effect is as likely to hurt as to help. In other words, it is a net of zero. So Darwinism remains great at “seeing” the immediately-next step, but it has no reliable power to see beyond. Finally and most importantly, recall the central message of  The Edge of Evolution: The Search for the Limits of Darwinism: To have a good idea of what Darwinian evolution can do, we no longer need to rely solely on speculative models, which may overlook or misjudge aspects of biology that nature would encounter. We already have good data in hand. We already have results that should constrain models. Over many thousands of generations, astronomical numbers of malarial cells seem not to have been able to take advantage of the look-ahead effect or anything else to build new, coherent molecular machinery. All that’s been seen in that system in response to antibiotics are a few point mutations. In tens of thousands of generations, with a cumulative population size in the trillions, no coherent new systems have been seen in the fascinating work of Richard Lenski on the laboratory evolution of E. coli. Instead, even beneficial mutations have turned out to be degradative ones, where previously functioning genes are deleted or made less effective. And that’s the same result as has been seen in the human genome in response to selective pressure due to malaria — a number of degraded genes or regulatory elements, and no new machinery.Theoretical models must be constrained by data. If models don’t reproduce what we do know happens in adaptive molecular evolution, then they are wholly unreliable in telling us anything about what we don’t know. Unless a model can also reproduce empirical results such as those cited just above, it should be regarded as fanciful.
“The Old Enigma,” Part 2 of 3
8:45 AM PDT, April 1, 2009
Dear Readers, This post continues directly from Part 1. Koonin is clearly very impressed with the new paper, which he calls “brilliant” and “a genuinely important work that introduces a new and potentially major mechanism of evolution...” His enthusiasm is a good indication that the problem is a major one, and that no other papers exist which deal effectively with it. So what is the paper (a theoretical, mathematical-modeling study) about? When a mutationless gene is transcribed and translated into a protein, errors can creep in. It turns out that these error rates are much higher than for copying DNA. Using published mutation rates, Whitehead et al (2008) estimate that 1 in 10 standard-sized proteins will contain an error; that is, they will contain an amino acid that is not coded for by the gene. The authors call these “phenotypic mutations.” Inherited changes that occur in the DNA are called “genotypic mutations.” Now, the idea is this. Suppose an organism needs two mutations to acquire some new feature, such as a disulfide bond. Further suppose that a single organism in a population that initially has neither of the mutations acquires just one of the necessary mutations in its DNA. Because of phenotypic mutations, this single organism will also contain some copies of the protein that have the second mutation. If the selective benefit of these phenotypic mutations is proportional to their concentration, as the authors suppose, then that organism may have an advantage over other organisms with no mutations. In a sense, the authors say, evolution can look a step ahead, so the authors dub this the “look-ahead effect.” The reviewer Eugene Koonin agrees that the paper “in a sense, overturns the old adage of evolution having no foresight. It seems like, even if non-specifically and unwittingly, some foresight might be involved.” As the authors and one of the other referees note, this is pretty reminiscent of something called the “Baldwin effect”, which was first proposed in the 19th century. The authors contend that there are subtle differences between the Baldwin effect and the look-ahead effect. Yet, whoever deserves priority for the idea, I don’t think the look-ahead effect contributes much at all to solving the problem of multiple mutations. In my own opinion, the idea of the paper is certainly clever, but Koonin vastly overestimates its importance. It offers virtually no help in solving the “old enigma,” as I explain below and in Part 3. First, the effect is quite minor at best. Since, based on transcriptional and translational mutation rates, the fraction of proteins with the correct phenotypic mutation is expected to be about one-hundredth of one percent (10^-4) of the total number of protein copies, the presumed selective effect will be only 10^-4 times the selective effect of the double genotypic mutant. So if the double genotypic mutant had a selective advantage of 0.1 (a pretty substantial value), the phenotypic look-ahead mutant would have an advantage of just 10^-5. If the double genotypic mutant has less of an advantage, the look-ahead has proportionately less. Because of this, the effect would be helpful only for large population sizes: too small of a population and there is no effect, because the mutation is effectively neutral. One can construct situations in which the selective advantage of a particular double genotypic mutant would be enormous (for example, if it conferred antibiotic resistance) so the look-ahead effect would be greater, but positing the general occurrence of such situations in nature amounts to special pleading. It’s also important to realize that the authors of the paper purposely did not consider mitigating factors in their analysis. As they wrote, “The goal of our analysis was to demonstrate that the look-ahead effect is theoretically possible, and as such, we intentionally excluded confounding factors for the sake of clarity.” Other possible important effects that weren’t considered in the model include the influence of the first genotypic mutation on the stability of the spectrum of proteins with phenotypic mutations, effects of the mutations on translation rates, and so on. It is certainly understandable to simplify a model as much as possible for an initial investigation. However, any confounding effects will only diminish the strength of an already-weak influence.
“The Old Enigma,” Part 1 of 3
11:55 AM PDT, March 31, 2009
Dear Readers, When The Edge of Evolution The Edge of Evolution: The Search for the Limits of Darwinism was first published, some Darwinist reviewers sneered that the problem it focused on — the need for multiple mutations to form some protein features (such as binding sites), where intermediate mutations were deleterious — was a chimera. There were no such things, they essentially said. University of Wisconsin geneticist Sean Carroll, reviewing the book for Science, stressed examples where intermediate mutations were beneficial (I never said there weren’t such cases, and discussed several in the book). In the same vein, University of Chicago evolutionary biologist Jerry Coyne assured readers of The New Republic that “[i]n fact, interactions between proteins, like any complex interaction, were certainly built up step by mutational step ... This process could have begun with weak protein-protein associations that were beneficial to the organism. These were then strengthened gradually...” The take-home message of the reviews for the public and for scientists in other fields was the same: Nothing to see here, folks. Move along. No problem here.Contrast those assurances with a recent paper that addresses “the old enigma [my italics] of the evolution of complex features in proteins that require two or more mutations.” Those words (reminiscent of the title of my 2004 paper in Protein Science with David Snoke, “Simulating evolution by gene duplication of protein features that require multiple amino acid residues,” which is cited by the recent paper) were written by the prominent bioinformatician (and no friend of ID) Eugene Koonin in his review of the paper, “The look-ahead effect of phenotypic mutations” (Whitehead, D. J., et al. 2008, Biol. Direct 3:18). (Reviews are published along with papers on the Biology Direct web site.)
Old enigma? Old enigma? Who knew that evolving just a couple of interactive amino acid residues was a long-standing mystery? Someone should tell Carroll and Coyne.... I will discuss the specifics of the paper in Part 2. But let me first drive home this point. The development of protein features, such as protein-protein binding sites, that require the participation of multiple amino acid residues is a profound, fundamental problem that has stumped the evolutionary biology community until the present day (and continues to do so, as I explain below). It is a fundamental problem because all proteins exert their effects by physically binding to something else, such as a small metabolite or DNA or other protein, and require multiple residues to do so. The problem is especially acute for protein-protein interactions, since most proteins in the cell are now known to act as teams of a half-dozen or more, rather than individually. Yet if one can’t explain how specific protein-protein interactions developed, then it is delusional to claim that we can explain how anything that depends on them developed, such as the molecular machinery of the cell. It’s like saying “we understand perfectly well how a car could evolve; we just don’t know how the pieces could get fit together.” If such a basic requirement for putting together complex systems is not understood, nothing is understood. Keep this in mind the next time you hear a blithe Darwinian tale about the undirected evolution of the cilium or bacterial flagellum. Waiting Longer for Two Mutations, Part 5
10:14 AM PDT, March 18, 2009
Dear Readers, An interesting paper appeared several months ago in an issue of the journal Genetics, “Waiting for Two Mutations: With Applications to Regulatory Sequence Evolution and the Limits of Darwinian Evolution” (Durrett, R & Schmidt, D. 2008. Genetics 180: 1501-1509). This is the fifth of five posts that discusses it. Cited references appear in this post. The final conceptual error that Durrett and Schmidt commit is the gratuitous multiplication of probabilistic resources. In their original paper they calculated that the appearance of a particular double mutation in humans would have an expected time of appearance of 216 million years, if one were considering a one kilobase region of the genome. Since the evolution of humans from other primates took much less time than that, Durrett and Schmidt observed that if the DNA “neighborhood” were a thousand times larger, then lots of correct regulatory sites would already be expected to be there. But, then, exactly what is the model? And if the relevant neighborhood is much larger, why did they model a smaller neighborhood? Is there some biological fact they neglected to cite that justified the thousand-fold expansion of what constitutes a “neighborhood,” or were they just trying to squeeze their results post-hoc into what a priori was thought to be a reasonable time frame? When I pointed this out in my letter, Durrett and Schmidt did not address the problem. Rather, they upped the stakes. They write in their reply, “there are at least 20,000 genes in the human genome and for each gene tens if not hundreds of pairs of mutations that can occur in each one.” The implication is that there are very, very many ways to get two mutations. Well, if that were indeed the case, why did they model a situation where two particular mutations — not just any two — were needed? Why didn’t they model the situation where any two mutations in any of 20,000 genes would suffice? In fact, since that would give a very much shorter time span, why did the journal Genetics and the reviewers of the paper let them get away with such a miscalculation? The answer of course is that in almost any particular situation, almost all possible double mutations (and single mutations and triple mutations and so on) will be useless. Consider the chloroquine-resistance mutation in malaria. There are about 10^6 possible single amino acid mutations in malarial parasite proteins, and 10^12 possible double amino acid mutations (where the changes could be in any two proteins). Yet only a handful are known to be useful to the parasite in fending off the antibiotic, and only one is very effective — the multiple changes in PfCRT. It would be silly to think that just any two mutations would help. The vast majority are completely ineffective. Nonetheless, it is a common conceptual mistake to naively multiply postulated “helpful mutations” when the numbers initially show too few. Here’s a final important point. Genetics is an excellent journal; its editors and reviewers are top notch; and Durrett and Schmidt themselves are fine researchers. Yet, as I show above, when simple mistakes in the application of their model to malaria are corrected, it agrees closely with empirical results reported from the field that I cited. This is very strong support that the central contention of The Edge of Evolution is correct: that it is an extremely difficult evolutionary task for multiple required mutations to occur through Darwinian means, especially if one of the mutations is deleterious. And, as I argue in the book, reasonable application of this point to the protein machinery of the cell makes it very unlikely that life developed through a Darwinian mechanism. References 1. White, N. J., 2004 Antimalarial drug resistance. J. Clin. Invest. 113: 1084–1092. 2. Lynch, M. and Conery, J.S. 2000. The evolutionary fate and consequences of duplicate genes. Science 290: 1151–1155.
Waiting Longer for Two Mutations, Part 4
10:11 AM PDT, March 13, 2009
Dear Readers, An interesting paper appeared several months ago in an issue of the journal Genetics, “Waiting for Two Mutations: With Applications to Regulatory Sequence Evolution and the Limits of Darwinian Evolution” (Durrett, R & Schmidt, D. 2008. Genetics 180: 1501-1509). This is the fourth of five posts that discusses it. Cited references will appear in the last post. Now I’d like to turn to a couple of other points in Durrett and Schmidt’s reply which aren’t mistakes with their model, but which do reflect conceptual errors. As I quote in a previous post, they state in their reply, “This conclusion is simply wrong since it assumes that there is only one individual in the population with the first mutation.” I have shown previously that, despite their assertion, my conclusion is right. But where do they get the idea that “it assumes that there is only one individual in the population with the first mutation”? I wrote no such thing in my letter about “one individual”. Furthermore, I “assumed” nothing. I merely cited empirical results from the literature. The figure of 1 in 10^20 is a citation from the literature on chloroquine resistance of malaria. Unlike their model, it is not a calculation on my part. Right after this, in their reply Durrett and Schmidt say that the “mistake” I made is a common one, and they go on to illustrate “my” mistake with an example about a lottery winner. Yet their own example shows they are seriously confused about what is going on. They write: “When Evelyn Adams won the New Jersey lottery on October 23, 1985, and again on February 13, 1986, newspapers quoted odds of 17.1 trillion to 1. That assumes that the winning person and the two lottery dates are specified in advance, but at any point in time there is a population of individuals who have won the lottery and have a chance to win again, and there are many possible pairs of dates on which this event can happen.... The probability that it happens in one lottery 1 year is ~1 in 200.” No kidding. If one has millions of players, and any of the millions could win twice on any two dates, then the odds are certainly much better that somebody will win on some two dates then that Evelyn Adams win on October 23, 1985 and February 13, 1986. But that has absolutely nothing to do with the question of changing a correct nucleotide to an incorrect one before changing an incorrect one to a correct one, which is the context in which this odd digression appears. What’s more, it is not the type of situation that Durrett and Schmidt themselves modeled. They asked the question, given a particular ten-base-pair regulatory sequence, and a particular sequence that is matched in nine of ten sites to the regulatory sequence, how long will it take to mutate the particular regulatory sequence, destroying it, and then mutate the particular near-match sequence to a perfect-match sequence? What’s even more, it is not the situation that pertains in chloroquine resistance in malaria. There several particular amino acid residues in a particular protein (PfCRT) have to mutate to yield effective resistance. It seems to me that the lottery example must be a favorite of Durrett and Schmidt’s, and that they were determined to use it whether it fit the situation or not.
Waiting Longer for Two Mutations, Part 3
2:35 PM PDT, March 11, 2009
Dear Readers, An interesting paper appeared several months ago in an issue of the journal Genetics, “Waiting for Two Mutations: With Applications to Regulatory Sequence Evolution and the Limits of Darwinian Evolution” (Durrett, R & Schmidt, D. 2008. Genetics 180: 1501-1509). This is the third of five posts that discusses it. Cited references will appear in the last post. The third problem also concerns the biology of the system. I’m at a bit of a loss here, because the problem is not hard to see, and yet in their reply they stoutly deny the mistake. In fact, they confidently assert it is I who am mistaken. I had written in my letter, ‘‘... their model is incomplete on its own terms because it does not take into account the probability of one of the nine matching nucleotides in the region that is envisioned to become the new transcription-factor-binding site mutating to an incorrect nucleotide before the 10th mismatched codon mutates to the correct one.’’ They retort, “This conclusion is simply wrong since it assumes that there is only one individual in the population with the first mutation.” That’s incorrect. Let me explain the problem in more detail. Consider a string of ten digits, either 0 or 1. We start with a string that has nine 1's, and just one 0. We want to convert the single 0 to a 1 without switching any of the 1's to a zero. Suppose that the switch rate for each digit is one per hundred copies of the string. That is, we copy the string repeatedly, and, if we focus on a particular digit, about every hundredth copy or so that digit has changed. Okay, now cover all of the numbers of the string except the 0, and let a random, automated procedure copy the string, with a digit-mutation rate of one in a hundred. After, say, 79 copies, we see that the visible 0 has just changed to a 1. Now we uncover the rest of the digits. What is the likelihood that one of them has changed in the meantime? Since all the digits have the same mutation rate, then there is a nine in ten chance that one of the other digits has already changed from a 1 to a 0, and our mutated string still does not match the target of all 1's. In fact, only about one time out of ten will we uncover the string and find that no other digits have changed except the visible digit. Thus the effective mutation rate for transforming the string with nine matches out of ten to a string with ten matches out of ten will be only one tenth of the basic digit-mutation rate. If the string is a hundred long, the effective mutation rate will be one-hundredth the basic rate, and so on. (This is very similar to the problem of mutating a duplicate gene to a new selectable function before it suffers a degradative mutation, which has been investigated by Lynch and co-workers. (2)) So, despite their self-assured tone, in fact on this point Durrett and Schmidt are “simply wrong.” And, as I write in my letter, since the gene for the chloroquine resistance protein has on the order of a thousand nucleotides, rather than just the ten of Durrett and Schmidt’s postulated regulatory sequence, the effective rate for the second mutation is several orders of magnitude less than they thought. Thus with the, say, two orders of magnitude mistake here, the factor of 30 error for the initial mutation rate, and the four orders of magnitude for mistakenly using a neutral model instead of a deleterious model, Durrett and Schmidt’s calculation is a cumulative seven and a half orders of magnitude off. Since they had pointed out that their calculation was about five million-fold (about six and a half orders of magnitude) lower than the empirical result I cited, when their errors are corrected the calculation agrees pretty well with the empirical data.
Waiting Longer for Two Mutations, Part 2
9:50 AM PDT, March 10, 2009
Dear Readers, An interesting paper appeared several months ago in an issue of the journal Genetics, “Waiting for Two Mutations: With Applications to Regulatory Sequence Evolution and the Limits of Darwinian Evolution” (Durrett, R & Schmidt, D. 2008. Genetics 180: 1501-1509). This is the second of five posts that discusses it. Cited references will appear in the last post. Interesting as it is, there are some pretty serious problems in the way they applied their model to my arguments, some of which they owned up to in their reply, and some of which they didn’t. When the problems are fixed, however, the resulting number is remarkably close to the empirical value of 1 in 10^20. I will go through the difficulties in turn. The first problem was a simple oversight. They were modeling the mutation of a ten-nucleotide-long binding site for a regulatory protein in DNA, so they used a value for the mutation rate that was ten-times larger than the point mutation rate. However, in the chloroquine-resistance protein discussed in The Edge of Evolution, since particular amino acids have to be changed, the correct rate to use is the point mutation rate. That leads to an underestimate of a factor of about 30 in applying their model to the protein. As they wrote in their reply, “Behe is right on this point.” I appreciate their agreement here. The second problem has to do with their choice of model. In their original paper they actually developed models for two situations — for when the first mutation is neutral, and for when it is deleterious. When they applied it to the chloroquine-resistance protein, they unfortunately decided to use the neutral model. However, it is very likely that the first protein mutation is deleterious. As I wrote discussing a hypothetical case in Chapter 6 of The Edge: “Suppose, however, that the first mutation wasn’t a net plus; it was harmful. Only when both mutations occurred together was it beneficial. Then on average a person born with the mutation would leave fewer offspring than otherwise. The mutation would not increase in the population, and evolution would have to skip a step for it to take hold, because nature would need both necessary mutations at once.... The Darwinian magic works well only when intermediate steps are each better (‘more fit’) than preceding steps, so that the mutant gene increases in number in the population as natural selection favors the offspring of people who have it. Yet its usefulness quickly declines when intermediate steps are worse than earlier steps, and is pretty much worthless if several required intervening steps aren’t improvements.” If the first mutation is indeed deleterious, then the model that Durrett and Schmidt (2008) applied to the chloroquine-resistance protein is wrong. In fact, if the parasite with the first mutation is only 10% as fit as the unmutated parasite, then the population-spreading effect they calculate for neutral mutations is pretty much eliminated, as their own model for deleterious mutations shows. What do the authors say in their response about this possibility? “We leave it to biologists to debate whether the first PfCRT mutation is that strongly deleterious.” In other words, they don’t know; it is outside their interest as mathematicians. (Again, I appreciate their candor in saying so.) Assuming that the first mutation is seriously deleterious, then their calculation is off by a factor of 10^4. In conjunction with the first mistake of 30-fold, their calculation so far is off by five-and-a-half orders of magnitude.
Waiting Longer for Two Mutations, Part 1
11:30 AM PDT, March 9, 2009
Dear Readers, An interesting paper appeared several months ago in an issue of the journal Genetics, “Waiting for Two Mutations: With Applications to Regulatory Sequence Evolution and the Limits of Darwinian Evolution” (Durrett, R & Schmidt, D. 2008. Genetics 180: 1501-1509). This is the first of five posts that discusses it. Cited references will appear in the last post. As the title implies, it concerns the time one would have to wait for Darwinian processes to produce some helpful biological feature (here, regulatory sequences in DNA) if two mutations are required instead of just one. It is a theoretical paper, which uses models, math, and computer simulations to reach conclusions, rather than empirical data from field or lab experiments, as The Edge does. The authors declare in the abstract of their manuscript that they aim “to expose flaws in some of Michael Behe’s arguments concerning mathematical limits to Darwinian evolution.” Unsurprisingly (bless their hearts), they pretty much do the exact opposite. Since the journal Genetics publishes letters to the editors (most journals don’t), I sent a reply to the journal. I waited until the reply, and a response from the authors, was published in Genetics until posting about it here on my blog. The original paper by Durrett and Schmidt can be found here, my response here, and their reply here. In their paper (as I write in my reply), “They develop a population genetics model to estimate the waiting time for the occurrence of two mutations, one of which is premised to damage an existing transcription-factor-binding site, and the other of which creates a second, new binding site within the nearby region from a sequence that is already a near match with a binding site sequence (for example, 9 of 10 nucleotides already match).” The most novel point of their model is that, under some conditions, the number of organisms needed to get two mutations is proportional not to the inverse of the square of the point mutation rate (as it would be if both mutations had to appear simultaneously in the same organism), but to the inverse of the point mutation rate times the square root of the point mutation rate (because the first mutation would spread in the population before the second appeared, increasing the odds of getting a double mutation). To see what that means, consider that the point mutation rate is roughly one in a hundred million (1 in 10^8). So if two specific mutations had to occur at once, that would be an event of likelihood about 1 in 10^16. On the other hand, under some conditions they modeled, the likelihood would be about 1 in 10^12, ten thousand times more likely than the first situation. Durrett and Schmidt (2008) compare the number they got in their model to my literature citation (1) that the probability of the development of chloroquine resistance in the malarial parasite is an event of order 1 in 10^20, and they remark that it “is 5 million times larger than the calculation we have just given.” The implied conclusion is that I have greatly overstated the difficulty of getting two necessary mutations. In the next several posts I will show that they are incorrect.
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Bio
I am Professor of Biological Sciences at Lehigh University in Pennsylvania. I received my Ph.D. in Biochemistry from the University of Pennsylvania in 1978. My current research involves delineation of design and natural selection in protein structures. In addition to teaching and research I work as a senior fellow with the Discovery Institute’s Center for Science & Culture.
In addition to publishing over 35 articles in refereed biochemical journals, I have also written editorial features in Boston Review, American Spectator, and The New York Times. My book, Darwin's Black Box, discusses the implications for neo-Darwinism of what I call "irreducibly complex" biochemical systems and has sold over 250,000 copies. The book was internationally reviewed in over one hundred publications and recently named by National Review and World magazine as one of the 100 most important books of the 20th century. I have presented and debated my work at major universities throughout North America and England.
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