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Antibody affinity maturation as an engineering process (and other things)

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In Kairosfocus’ very good thread about functional complexity, I posted about antibody affinity maturation as an example of a very complex engineering process embedded in biological beings. Both Kairosfocus and Dionisio suggested that I could open a new thread to discuss the issue. When such good friends ask, I can only comply.  🙂

For lack of time, I will try to be very simple.

First of all, I paste here my original post (#6 in the original thread):

KF:

Thank you for the very good summary. Among many other certainly interesting discussions, we may tend to forget sometimes that functionally specified complex information is the central point in ID theory. You are very good at reminding that to all here.

I would like to suggest a very good example of multilevel functional complexity in biology, which is often overlooked. It is an old favourite of mine, the maturation of antibody affinity after the initial immunological response.

Dionisio has recently linked an article about a very recent paper. The paper is not free, but I invite all those interested to look at the figures and legends, which can be viewed here:

http://www.nature.com/nri/jour…..28_ft.html

The interesting point is that the whole process has been defined as “darwinian”, while it is the best known example of functional protein engineering embedded in a complex biological system.

In brief, the specific B cells which respond to the epitope (antigen) at the beginning of the process undergo a sequence of targeted mutations and specific selection, so that new cells with more efficient antibody DNA sequences can be selected and become memory cells or plasma cells.

The whole process takes place in the Germinative Center of lymph nodes, and involves (at least):

1) Specific B cells with a BCR (B cell receptor) which reacts to the external epitope.

2) Specific T helper cells

3) Antigen presenting cells (Follicular dendritic cell) which retain the original epitope (the external information) during the whole process, for specific intelligent selection of the results

4) Specific, controlled somatic hypermutation of the Variable region of the Ig genes, implemented by the following molecules (at least):

a) Activation-Induced (Cytidine) Deaminase (AID): a cytosine:guanine pair is directly mutated to a uracil:guanine mismatch.

b) DNA mismatch repair proteins: the uracil bases are removed by the repair enzyme, uracil-DNA glycosylase.

c) Error-prone DNA polymerases: they fill in the gap and create mutations.

5) The mutated clones are then “measured” by interaction with the epitope presented by the Follicular DC. The process is probably repeated in multiple steps, although it could also happen in one step.

6) New clones with reduced or lost affinity are directed to apoptosis.

7) New clones with higher affinity are selected and sustained by specific T helper cells.

In a few weeks, the process yields high affinity antibody producing B cells, in the form of plasma cells and memory cells.

You have it all here: molecular complexity, high control, multiple cellular interactions, irreducible complexity in tons, spacial and temporal organization, extremely efficient engineering. The process is so delicate that errors in it are probably the cause of many human lymphomas.

Now, that’s absolute evidence for Intelligent Design, if ever I saw it. :)

The most interesting answers came from Aurelio Smith and sparc. I have already answered AS’s comment in the original thread. Spark’s comments were more specific, so I paste them here  (#58 and 59):

You haven’t looked up evolution of AID, did you?

and

BTW, you let out the part of the B-cell development that occurs without any antigen. Lots of mutations, rearragements and selection. Where and how does ID interfere in these processes. Especially, in cases of man made synthetic artificial antigens that were not present 50 years ago?

OK, I will make just a couple of comments on these two points here, and let the rest to the discussion:

a) My point was not specifically about the evolution of the individual proteins in the system, but about the amazing complexity of the whole system. So, I have not done any detailed analysis of the individual proteins I quote. However, I will look at that aspect. As sparc seems aware of specific information about the evolution of AID, I invite him ot provide some references, and we can certainly go on from there.

b) I did not “let out” the part of the B-cell development. I simply focused on affinity maturation. However, the part sparc alludes to is extremely interesting too, so I will mention here in very general lines how it works, and why it is another wonderful example of intelligent engineering. And we can obviously discuss this second aspect too.

In brief, the adaptive immune system must solve the problem of reacting t a great number of potential antigens/epitope, which are not known in advance (I will use “epitope” from now on, because that is the immulogically active part of an antigen).

So, the two branches of the adaptive immune system (B system and T system) must be “prepared” to recognized possible epitopes coming from the outer world. They do that by a “sensor” which is the B cel receptor (BCR) in the B system, and the T cell receptor (TCR) in the T system.

Let’s focus the discussion on the B system.

To recognize the greatest number of possible epitopes (IOWs, of possible small biochemical configurations, mainly of proteins but also of other molecules), the B immune system builds what is usually known as the “basic repertoire”.Very simply, B cells underso a process of somatic genetic differentiation, essentially based on the recombination of VDJ genes, which generates a basic repertoire of different B clones with specific variable genes for the heavy and light chain, IOWs a specific BCR. In that sense, immune cells are different from other somatic cells, because they have a specific genetic recombination of the variable chains of the BCR (and therefore of the antibody that they will produce.

No one knows exactly how big that repertoire is in each individual, but new techniques are helping much in studying it quantitatively. From what I have read, I would say that the size is probably somewhere between 10^6 and 10^9 (more or less the total number of B cells in an organism).

Now, what is the purpose of this basic BCR (antibody) repertoire? We can consider it as a “network” of lower affinity antibodies covering in a loose way the space of possible epitope configurations. That repertoire is generated blindly (IOWs, without any information about specific antigens) by a process of sophisticated genetic engineering (VDJ recombination and other factors), which again uses random variation in a controlled way to generate diversity.

So, to sum up. two different complex algorithms act to ensure efficient immune responses.

1) The first one generates a “blind” repertoire of lower affinity antibodies covering as well as possible the whole space of configurations of possible epitopes.

2) The second one (affinity maturation) refines the affinity of the B cells selected in the primary response (from the basic repertoire) so that they become high affinity, specialized memory cells. This is the process I described in the beginning, in my post.

Both processes are wonderful examples of sophisticated engineering and irreducibly complex systems, and they are completely different one from the other. Both processes work together in sequence in a sophisticated and irreducibly complex meta-system.

Both use controlled random variation to generate diversity. The second process also uses intelligent selection based on existing information from the environment (the epitope conserved in the Follicular GC cell).

All that is very brief, and in no way covers the whole complexity of what is known. So, let’s open the discussion.

Comments
gpuccio Your OP has been visited 1170 times so far. There are 460+ follow-up comments. However, not a single counterargument for the challenge referenced in post #440. Even sparc has let us down, after triggering your OP. Does that mean that your ‘nice’ interlocutors lack serious arguments to post here? Oh, well… there’s not much we can do about it. :)Dionisio
February 18, 2015
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...and anyone interest in further research can download the Matlab package here: A matlab package to sample high-dimensional parameter spaces A matlab toolbox to determine the robustness Me_Think
February 18, 2015
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Yes Me Think, it was intelligently designed to be robust. That robustness allows for alternative splicing, overlapping genes and RNA splicing and editing. And it remains that your doesn't have a mechanism capable of producing living organisms, let alone the genetic, regulatory and metabolic networks.Joe
February 18, 2015
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...And here's the bit on robustness. Combined with hyperdimension, the search network reduces probability of finding new functions to almost nil- unlike ID's 'improbable search landscape'. Now ID can't claim search is improbable.
Robustness isn’t limited to metabolism and whole genomes. It is just as pervasive in individual proteins like lysozyme. This protein kills bacteria by destroying their wall of protective molecules. It appears not only in human saliva, tears, and even mother’s milk, but in a large number of other animals, and even in viruses that attack bacteria.13 When scientists want to find out how a protein like this works, they do something akin to knocking out genes in a genome, but on a smaller scale—they change individual letters in the protein’s amino acid string and observe the effects of each change. When they engineered more than two thousand lysozyme variants, each one with a single altered amino acid, they found that some sixteen hundred variants—more than 80 percent—could still kill bacteria. Proteins like lysozyme, and there are many, are as robust as metabolisms. And the same holds for regulation circuits—we already heard about a circuit in the bacterium Escherichia coli that can be rewired in the laboratory without ill effects (chapter 5). The most obvious benefit of such robustness is that it keeps organisms alive. Its importance goes back all the way to the first self-replicating RNA molecules and the fatal error catastrophe, in which small errors compound over time until replication becomes impossible (chapter 2). That was a true catch-22: RNA molecules have to self-replicate with few errors to acquire the ability to self-replicate with few errors. But only a bit of the obustness in today’s RNA could lower the bar for this problem to a manageable height: Because a few replication errors in a robust molecule do not erode its ability to self-replicate, robustness provides a stay of execution by error catastrophe, perhaps long enough to stumble upon better replicators.14 But the importance of robustness goes far beyond that. It explains the mystery of genotype networks and of innovability.
Me_Think
February 18, 2015
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genotype networks DO NOT EMERGE OVER TIME
That negates Darwinism and any step-by-step story of origins.Silver Asiatic
February 18, 2015
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Me Think- your position still doesn't have a mechanism capable of producing biological reproducersJoe
February 18, 2015
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Right Just read further along to here:
A ball with constant radius occupies ever-decreasing and ever-tinier fractions of a cube’s volume.32 (This volume decreases not just for my example of a 15 percent ratio of volumes, but for any ratio, even one as high as 75 percent, where the volume drops to 49 percent in three dimensions, to 28 percent in four, to 14.7 percent in five, and so on, to ever-smaller fractions.)33 The same counterintuitive phenomenon holds in other libraries of innovation: The more dimensions they have—the larger their collection of metabolisms or molecules—the smaller the distance to find specific innovations. A browser who starts with a metabolism that can survive on some foods and then blindly searches for one that can thrive on others needs to change only a few reactions and explore a tiny fraction—too small to imagine—of the metabolic library before stumbling upon the right text. The same holds true for RNA. Starting from an existing RNA molecule, a nearby molecule with a new shape—any new shape you choose—will be found after changing only a few of the molecule’s nucleotide building blocks and having explored a tiny fraction of the library.34 The astonishing fact that evolution needs to explore one 10-100th of a library to secure the arrival of the fittest goes a long way to explain how blind search produces life’s immense diversity. Evolution does not have to search the entire haystack, because the haystack contains more than one needle. In fact, thanks to robustness, and the genotypic disorder it permits, the haystack contains too many needles to count, and they are organized into sprawling but navigable networks.
Funny, how it negates the oft repeated 'Needle in Haystack' ID position.Me_Think
February 18, 2015
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Me_Think #455: Why don’t you start reading chapter 6 (..)?
That's a weird request, since the quote I provided in post #453 is from CHAPTER SIX, "The Hidden Architecture".Box
February 18, 2015
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Box, Keep reading. The book is for general audience. It gets into hypercubes and network search only later. Why don't you start reading chapter 6 to see how search space reduces, and as quoted by you earlier: Evolution can reach them in a few small steps, minor edits in a genotype. Me_Think
February 18, 2015
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genotype networks DO NOT EMERGE OVER TIME. They exist in the timeless eternal realm of nature’s libraries.
That's great science. There's a timeless and eternal realm where genotype networks exist. And libraries arise all by themselves. That's a pretty important part of the story of origins, I'd think.Silver Asiatic
February 18, 2015
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Okay, how do genotype networks come into existence? Well, according to Wagner, by "self-organization" in the "timeless eternal realm of nature’s libraries". Makes perfect sense, right? This is great stuff.
Wagner: Genotype networks are yet another example of the pervasive self-organization we first encountered in chapter 2—the same phenomenon that pervades both the living and nonliving worlds, from the formation of galaxies to the assembly of membranes. But they are a peculiar example of self-organization. Unlike galaxies, which self-assemble through the gravitational attraction of cosmic matter, or biological membranes, which self-organize through the love-hate relationship of lipid molecules with water, genotype networks DO NOT EMERGE OVER TIME. They exist in the timeless eternal realm of nature’s libraries. [FAR OUT MAN!] But they certainly have a form of organization—so complex that we are just beginning to understand it—and this organization arises all by itself [Of course! That goes without saying. SURE THING] And as with galaxies and membranes, the principle behind their self-organization is simple: Life is robust. This robustness is both necessary for genotype networks—otherwise synonymous texts would be isolated from one another—and it is sufficient.17 Wherever metabolisms, proteins, and regulatory circuits are robust, genotype networks emerge. [My emphasis]
Box
February 18, 2015
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Me Think- what is your point? Your position doesn't have a mechanism capable of producing metabolism.Joe
February 18, 2015
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ID ers, Sigh.There are 5,500 metabolic pathways. You can explore all the pathways at biocyc These are represented by the hypothetical library (Just like landscapes in Dembski, Axe papers).If you ever feel like looking up Wagner's papers, data and software, you will understand that structural dimensions run into millions! You can get software, research data at: Wagner's Zurich univ page Get into the habit of reading something other than Marvel comics if you need to understand anything useful.Me_Think
February 18, 2015
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gpuccio Your OP has been visited 1166 times so far. There are 450 follow-up comments. However, not a single counterargument for the challenge described @440. It seems like your 'nice' interlocutors lack serious arguments to post here. Oh, well... there's not much we can do about it. :)Dionisio
February 18, 2015
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Box: "I have a hard time reading Wagner and keep a straight face." There is no need to keep a straight face. I hope we are still allowed to laugh, in this world. It's a precious part of our libertarian free will.gpuccio
February 18, 2015
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I will say it again: Borges was a great poet, and his vision of the Library of Babel has more beauty and sincere desperation in itself than all the arrogant pseudo-scientific constructions of multiverses and multidimensional hypercubes.gpuccio
February 18, 2015
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Box: Wagner's reasoning, in a nutshell, as I see it: Biological objects and human artifacts both have similar properties. They both seem designed. But, as we cannot accept that biological objects are designed, we could propose that human artifacts are, after all, the result of universal darwinism.gpuccio
February 18, 2015
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In other words, we can arrange the library’s metabolic texts on the corners of a hypercube in a 5,000-dimensional space. This is why off-the-shelf shelving would not work. You cannot cram the metabolic library into three puny dimensions. It needs thousands of dimensions to breathe.
I think it would be a lot better if we arranged the library into a 50,000 dimension space. That way each 'metabolic text' would have ten times more opportunities only one step away.Silver Asiatic
February 18, 2015
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Me_Think: This is from one of the most recent papers by Wagner:
The points of correspondence between biology and technology we discussed are far from complete [32,67,122]. However, they already insinuate that highly successful biological and technological systems share a property that is independent of both biology and technology. This property, one might call it innovability, emerges from the organization of a space of possible innovations, designs or genotypes [6]. Because such spaces are mathematical concepts, one could easily dismiss them and their organization as figments of our imagination, were it not for what Nobel laureate Eugene Wigner called the ‘unreasonable effectiveness of mathematics’ in explaining the natural world [123]. It suggests that such spaces and the innovations therein have an existence beyond our limited minds. And while concepts such as this, for more than two millennia, were the subject of non-experimental disciplines such as mathematics and philosophy, they have now become accessible to experimental science. For example, recent technological advances in biology permit the synthesis of arbitrary new protein genotypes. In doing so, they also permit the exploration of a genotypes space through experiment and computation [124–126]. Technological systems are not far behind, as explorations of digital circuit spaces testify [119,127]. Efforts such as this will undoubtedly accelerate the demolition of the conceptual wall separating biological and technological innovation.
And he is perfectly right. There is no conceptual wall separating biological and technological innovation: both are examples of design.gpuccio
February 18, 2015
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Dionisio #442, I have a hard time reading Wagner and keep a straight face. This guy not only assumes that DNA and metabolic texts (the “hyperastronomical library”) is somehow organized in a 5,000-dimensional space, but also assumes the existence of "genotype networks". Why do they exist? For the same reason that 5000-dimensional space exists: otherwise things don't work.
Wagner: Viewed from afar, the library’s explorers, from bacteria to blue whales, might appear like giant clouds of dust grains—dwarfed by the library itself—drifting this way and that, from one stack to the next, endlessly meandering swirls of living things that try new combinations of chemical reactions over and over and over again. Some die. Others survive, and pass innovative combinations on to subsequent generations. This churning mass of life is evolution in action. That action would vanish if genotype networks did not exist.
Is there a (scientific) way to detect "genotype networks" in 5,000-dimensional space? I guess not, but Wagner doesn't seem worried about those details. Where does the information in the “hyperastronomical library” and the "genotype networks" come from? As far as I can tell Wagner doesn't offer any explanation. -- edit: Gpuccio, Wagner comes across as a guy who never parted with the crazy ideas of the hippie movement.Box
February 18, 2015
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Box: I still find Wagner's ideas irrelevant. Maybe Me-Think will convince me of the opposite. Moreover, he goes on discussing metabolisms, as though they were existing building stones. What about the complex proteins which make those metabolisms possible? Maybe if we arrange them in a 10000-dimensional icosahedron, it will be easy to find new functional proteins for all necessities. We should alert protein engineers of that intriguing possibility.gpuccio
February 18, 2015
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#441 Box Within the main topic of this thread: Can you, Wagner or anybody else provide at least one reference to any paper that presents a serious, comprehensive, logically coherent counterargument for what gpuccio wrote in the OP, and later in posts 326, 327, 394, 436? Can you, Wagner or anybody else provide at least one reference to any paper that can seriously answer the questions in post #157?Dionisio
February 18, 2015
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Wagner terms DNA an "hyperastronomical library".
Wagner: The deepest secrets of nature’s creativity reside in libraries just like this: all-encompassing and hyperastronomically large. Only instead of being written in human language, the texts in these libraries are written in the genetic alphabet of DNA and the molecular functions that DNA encodes. The library’s chemical language can express life itself—all of it.
The problem is how to find anything in this huge library.
Wagner: The problem is much worse in a hyperastronomical library. The universal library might well contain the secret to immortality—or at least the perfect recipe for turkey stuffing—yet the library is so large that we would never find it unless we knew where to look.
The solution: assume that the library is a 5000-dimensional space and everything can be found in a few steps.
Wagner: In other words, we can arrange the library’s metabolic texts on the corners of a hypercube in a 5,000-dimensional space. This is why off-the-shelf shelving would not work. You cannot cram the metabolic library into three puny dimensions. It needs thousands of dimensions to breathe. (…) And what holds for one corner of the cube holds for any other corner: It has three neighbors. Likewise, in a 5,000-dimensional cube, each and every metabolism has as many neighbors as there are dimensions, five thousand in all. You can walk from each metabolic text in five thousand different directions, to find one of its five thousand neighbors in a single step. (…) Evolving organisms are like visitors to the metabolic library. Gene deletions and gene transfer allow them to walk through the library, to step from one metabolic text to another, often an immediate neighbor. (…) Evolution can reach them in a few small steps, minor edits in a genotype.
Box
February 18, 2015
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Ok, too much digression. Let's go back to the main topic of this discussion: Can Me_Think, Wagner or anybody else provide at least one reference to any paper that presents a serious, comprehensive, logically coherent counterargument for what gpuccio wrote in the OP, and later in posts 326, 327, 394, 436? Can Me_Think, Wagner or anybody else provide at least one reference to any paper that can seriously answer the questions in post #157?Dionisio
February 18, 2015
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gpuccio @ 438
Frankly, I don’t know his ideas in detail, and I cannot care less about them for what I have heard until now.
Well if you don't care about an Evolutionary Biologist's peer reviewed papers and how networked hyper dimension space demolishes silly Axe and Dembski's search algorithm and landscape arguments, what is the point of arguing at all ?!!!
And if you need time to “work it out”, please take all the time you need.
Since it involves taking derivative of hyperspace function and possibly Poly Gamma to see if a certain dimension will give maximum search area, it will take time, but I am not sure it is worth it. In any case I will work it out , may be to use in some other threadMe_Think
February 18, 2015
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Me_Think: Maybe Wagner knows what he is talking about when he talks of his personal ideas. He can well publish thousands of publications about his personal ideas. That does not imply that his ideas are true. Frankly, I don't know his ideas in detail, and I cannot care less about them for what I have heard until now. As far as your argument goes, as you have expressed it, apparently based, correctly or not, on hi, ideas, I can only repeat: it is silly, if you intend it as an argument applied to proteins and biology (as you seem to intend it). If you believe that what you said has any relevance to the points I highlighted in post #432, please express your ideas. I will be happy to hear them. And if you need time to "work it out", please take all the time you need. I am not CH, and as I have said, I am interested in arguments, not in individual persons (or numbers of publications).gpuccio
February 18, 2015
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gpuccio @ 432
We could simply say that the argument you offered is silly. Is that more clear? The simple problem is not that it is difficult to leave the functional island, but that the functional island is surrounded by oceans of non functional, non selectable configurations, and almost all of them are unrelated to possible highly complex functional and selectable configurations
You argued that
Wagner and you [Me_Think] don’t know what you are talking about.
By flaunting a long list of publications (which ID Scientists can't match),I showed he knows what he is talking about.What he researched and published in his book is what I have offered as an argument for landscape search. You , Axe etal. are essentially claiming that evolution is a white noise landscape. Wagner shows that by using network search in hyper-dimensional (which is nothing but the structural dimensions) search space, the improbabilities of searching vanishes . A more appropriate argument would be if you claim network search cannot be equated to landscape search and so volume search doesn't apply -only surface area of the search sphere should be used. May be I would be stumped ,or not - I would have to work that out.Me_Think
February 18, 2015
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Dionisio: "Does that get us the amazingly complex interwoven mechanisms that researchers see in the biological systems? IOW, the protein availability is a necessary condition, but is it sufficient, in order to have those elaborate cellular and molecular choreographies orchestrated within the biological systems? Are there other factors to consider?" No, it doesn't. No, it is not. And yes, there are. Let's say that we are in front of an amazing multilayered irreducible complexity. :)gpuccio
February 17, 2015
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Me_Think: A list of publications is not an argument, and is not guarantee of being right on a particular point. Do you believe differently? However, I was referring to your personal argument as offered by you quoting Wagner. I am not interested in people, but in arguments. We could simply say that the argument you offered is silly. Is that more clear? Now, please don't answer that with a list of your publications.gpuccio
February 17, 2015
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gpuccio @ 432
really think that Wagner and you don’t know what you are talking about.
Really ?
Publications (Peer Reviewed) 2014 160. Payne, J.L., Wagner, A. (2014) The robustness and evolvability of transcription factor binding sites. Science 343, 875-877.[link] 159. Wagner, A. (2014) A genotype network reveals homoplastic cycles of convergent evolution in influenza A (H3N2) evolution. Proceedings of the Royal Society B: Biological Sciences 281, 20132763. [reprint request] 158. Szovenyi, P., Devos, N., Weston, D.J., Yang, X., Hock, Z., Shaw, J.A., Shimizu, K.K., McDaniel, S., Wagner, A. Efficient purging of deleterious mutations in plants with haploid selfing. Genome Biology and Evolution 6, 1238-1252. [reprint request] 157. Wagner, A., Rosen, W. (2014) Spaces of the possible: universal Darwinism and the wall between technological and biological innovation. Journal of the Royal Society Interface 11, 20131190. [reprint request] 156. Payne, J.L., Wagner, A. Latent phenotypes pervade gene regulatory circuits. BMC Systems Biology 8 (1), 64. [reprint request] 155. Dhar, R., Bergmiller, T., Wagner, A. (2014) Increased gene dosage plays a predominant role in the initial stages of evolution of duplicate TEM-1 beta lactamase genes. Evolution 68, 1775-1791. [reprint request] 154. Hayden, E., Bratulic, S., Konig, I., Ferrada, E., Wagner, A. (2014) The effects of stabilizing and directional selection on phenotypic and genotypic variation in a population of RNA enzymes. Journal of Molecular Evolution 78, 101-108. [reprint request] 153. Barve, A., Hosseini, S.-R., Martin, O.C., Wagner, A. Historical contingency and the gradual evolution of metabolic properties in central carbon and genome-scale metabolisms. BMC Systems Biology 2014, 8:48. [reprint request] 152. Wagner, A. (2014) Mutational robustness accelerates the origin of novel RNA phenotypes through phenotypic plasticity. Biophysical Journal 106, 955-965. [reprint request] 151. Sunnaker, M., Zamora-Sillero, E., Garcia de Lomana, A.L., Rudroff, F., Sauer, U., Stelling, J., Wagner, A. (2014) Topological augmentation to infer hidden processes in biological systems. Bioinformatics 30, 221-227. [reprint request] 150. Wagner, A., Andriasyan, V., Barve, A. (2014) The organization of metabolic genotype space facilitates adaptive evolution in nitrogen metabolism. Journal of Molecular Biochemistry 3: 2-13. [reprint request] 149. Payne, J.L., Moore, J.H., Wagner, A. (2014) Robustness, evolvability, and the logic of genetic regulation. Artificial Life 20, 111-126. [reprint request] 2013 148. Barve, A., Wagner, A. (2013) A latent capacity for evolutionary innovation through exaptation in metabolic systems. Nature 500, 203-206. [reprint request] 147. Sunnaker, M., Zamora-Sillero, E., Dechant, R., Ludwig, C., Busetto, A.G., Wagner, A., Stelling, J. (2013) Automatic generation of predictive dynamic models reveals nuclear phosphorylation as the key Msn2 control mechanism. Science Signaling 6, ra41. [reprint request] 146. Szovenyi, P., Ricca, M., Hock, Z., Shaw, J.A., Shimizu, K.K., Wagner, A. (2013) Selection is no more efficient in haploid than in diploid life stages of an angiosperm and a moss. Molecular Biology and Evolution 30: 1929-1939. [reprint request] 145. Payne, J.A., Wagner, A. (2013) Constraint and contingency in multifunctional gene regulatory circuits. PLoS Computational Biology 9 (6), e1003071. [reprint request] 144. Dhar, R., Saegesser, R., Weikert, C., Wagner, A. (2013) Yeast adapts to a changing stressful environment by evolving cross-protection and anticipatory gene regulation. Molecular Biology and Evolution 30, 573-588. [reprint request] 143. Sabath, N., Ferrada, E., Barve, A., Wagner, A., (2013) Growth temperature and genome size in bacteria are negatively correlated, suggesting genomic streamlining during thermal adaptation. Genome Biology and Evolution 5, 966-977. [reprint request] . 142. Bilgin, T., Kurnaz, I.A., Wagner, A. (2013) Selection shapes the robustness of ligand-binding amino acids. Journal of Molecular Evolution 76, 343-349. [reprint request] . 141. Bichsel, M., Barbour, A.D., Wagner, A. (2013) Estimating the fitness effect of insertion sequences. Journal of Mathematical Biology 66, 95-114. [reprint request] 140. Wagner, A. (2013) Genotype networks and evolutionary innovations in biological systems. In Handbook of Systems Biology. Eds: Walhout, A.J.M., Vidal, M., Dekker, J., Academic Press, London, p 251-264. [reprint request] 139. Wagner, A. (2013) Metabolic networks and their evolution. In Encyclopedia of Systems Biology; p 1256-1259; Dubitzky, W., Wolkenhauer, O., Yokota, H., Cho, K.-H. (eds) Springer, New York. 2012 138. Barve, A., Rodrigues, J.F.M., Wagner, A. (2012) Superessential reactions in metabolic networks. Proceedings of the National Academy of Sciences of the U.S.A. 109 (18), E1121-E1130. [reprint request] 137. Wagner, A. (2012) The role of robustness in phenotypic adaptation and innovation. Proceedings of the Royal Society B: Biological Sciences 279, 1249-1258.[reprint request] 136. Hayden, E.J., Wagner, A. (2012) Environmental change exposes beneficial epistatic interactions in a catalytic RNA. Proceedings of the Royal Society B: Biological Sciences 279, 3418-3425.    135. Chen, B., Wagner, A. (2012) Hsp90 is important for fecundity, longevity, and buffering of cryptic deleterious variation in wild fly populations. BMC Evolutionary Biology 12, 25. [reprint request] 134. Wagner, A. (2012) The role of randomness in Darwinian evolution. Philosophy of Science 79, 95-119. [reprint request] 133. Sabath, N., Wagner, A., Karlin, D. (2012) Evolution of viral proteins originated de novo by overprinting. Molecular Biology and Evoluion 29, 3767-3780. 132. Guo, B., Zuo, M., Wagner, A. (2012) Pervasive indels and their evolutionary dynamics after the fish-specific genome duplication. Molecular Biology and Evolution. doi: 10.1093/molbev/mss108. [reprint request] 131. Bragg, J.G., Quigg, A., Raven, J.A., Wagner, A. (2012) Protein elemental sparing and codon usage bias are correlated among bacteria. Molecular Ecology 21, 2480–248. [reprint request] 130. Ferrada, E., Wagner, A. (2012) A comparison of genotype-phenotype maps for RNA and proteins. Biophysical Journal 102, 1916-1925. [reprint request] 129. Matias Rodrigues, J.F., Rankin, D., Rossetti, V., Wagner, A., Bagheri, H.C. (2012) Differences in cell division rates drive the evolution of terminal and differentiation in microbes. PLoS Computational Biology 8 (4), e1002468. [reprint request] 128. De la Chaux, N., Tsuchimatsu, T., Shimizu, K.K., Wagner, A. (2012) The predominantly selfing plant Arabidopsis thaliana experienced a recent reduction in transposable element abundance compared to its outcrossing relative Arabidopsis lyrata. Mobile DNA 3, 2. [reprint request] 127. Bilgin, T., Wagner, A. (2012) Design constraints on a synthetic metabolism. PLoS ONE 7(6): e39903. [reprint request] 126. Wagner, A. (2012) Metabolic networks and their evolution. Evolutionary Systems Biology/Advances in Experimental Medicine and Biology 751: 29-52. [reprint request] 125. Wagner, A. (2012) High dimensional adaptive landscapes facilitate evolutionary innovation p271-282 in Svensson, E.I., Calsbeek, R. (eds) The adaptive landscape in evolutionary biology. Oxford University Press, Oxford, UK. [reprint request] 124. Wagner, A., Weikert, C. (2012) Phenotypic constraints and phenotypic hitchhiking in a promiscuous enzyme. The Open Evolution Journal 6, 14-28. [reprint request] 123. Hayden, E., Wagner, A. (2012) Directional selection causes decanalization in a catalytic RNA. PLoS ONE 7(9), e45351. [reprint request] 2011 122. Hayden, E.J., Ferrada, E., Wagner, A. (2011) Cryptic genetic variation promotes rapid evolutionary adaptation in an RNA enzyme. Nature 474, 92-95.[reprint request] 121. Wagner, A. (2011) The molecular origins of evolutionary innovations. Trends in Genetics 27, 397-410. [reprint request] 120. Wagner, A. (2011) Genotype networks shed light on evolutionary constraints. Trends in Ecology and Evolution 26, 577-584. [reprint request] 119. Dhar, R., Sägesser, R., Weikert, C., Yuan, J., Wagner, A. (2011) Adaptation of Saccharomyces cerevisiae to saline stress through laboratory evolution. Journal of Evolutionary Biology 5, 1135-1153. [reprint request] 118. Wagner, A. (2011) The low cost of recombination in creating novel phenotypes. Bioessays 33, 636-646. [reprint request] 117. Zamora-Sillero, E. Hafner, M., Ibig, A., Stelling, J., Wagner, A. (2011) Efficient characterization of high-dimensional parameter spaces for systems biology. BMC Systems Biology 5, 142. [reprint request] 116. Samal, A., Wagner, A., Martin, O.C. (2011) Environmental versatility promotes modularity in large scale metabolic networks. BMC Systems Biology 5,135.[reprint request] 115. Espinosa-Soto, C. Martin, O.C., Wagner, A. (2011) Phenotypic plasticity can facilitate adaptive evolution in gene regulatory circuits. BMC Evolutionary Biology 11:5, doi:10.1186/1471-2148-11-5. [reprint request] 114. Rodrigues, J.F.M., Wagner, A. (2011) Genotype networks, innovation, and robustness in sulfur metabolism. BMC Systems Biology 5:39. [reprint request] 113. Raman, K., Wagner, A. (2011) The evolvability of programmable hardware. Journal of the Royal Society Interface 8: 269-281. [reprint request] 112. Raman, K., Wagner, A. (2011) Evolvability and robustness in a complex signaling circuit. Molecular BioSystems 7, 1081-1092. [reprint request] 111. De la Chaux, N., Wagner, A. (2011) BEL/Pao retrotransposons in metazoan genomes. BMC Evolutionary Biology 11 :154. [reprint request] 110. Wright, J., Bellissimi, E., de Hulster, E., Wagner, A., Pronk, J.T., van Maris, A.J.A. (2011) Batch and continuous culture-based selection strategies for acetic acid tolerance in xylose-fermenting Saccharomyces cerevisiae. FEMS Yeast Research 11,299–306. [reprint request] 109. Espinosa-Soto, C., Martin, O.C., Wagner, A. (2011) Phenotypic plasticity can increase phenotypic variability after non-genetic perturbations in gene regulatory circuits. Journal of Evolutionary Biology 24, 1284-1297. [reprint request] 108. Guo, B., Wagner, A., He, S. (2011) Duplicated gene evolution following whole-genome duplication in teleost fish. pp. 27-36. In: Friedberg, F. (ed.), Gene duplication. InTech, Rijeka, Croatia. [reprint request] 2010 107. Espinosa-Soto, C., Wagner, A. (2010) Specialization can drive the evolution of modularity. PloS Computational Biology 6: e1000719. [reprint request] 106. Samal, A., Matias Rodrigues, J.F.., Jost, J., Martin, O.C., Wagner, A. (2010) Genotype networks in metabolic reaction spaces. BMC Systems Biology 4:30. [reprint request] 105. Rankin, D.J., Bichsel, M. Wagner, A. (2010) Mobile DNA can drive lineage extinction in bacterial populations. Journal of Evolutionary Biology 23, 2422-2431. [reprint request] 104. Raman, K., Wagner, A. (2010) The evolvability of programmable hardware. Journal of the Royal Society, Interface. June 9, doi: 10.1098/rsif.2010.0212. [reprint request] 103. Ferrada, E., Wagner, A. (2010) Evolutionary innovations and the organization of protein functions in genotype space. PLoS ONE 5(11): e14172. doi:10.1371/journal.pone.0014172. [reprint request] 102. Bichsel, M., Barbour, A.D., Wagner, A. (2010) The early phase of an insertion sequence infection. Theoretical Population Biology 78, 278-288. [reprint request] 101. Sulc, P., Wagner, A., Martin, O.C. (2010) Quantifying slow evolutionary dynamics in RNA fitness landscapes. Journal of Bioinformatics and Computational Biology 8, 1027-1040. [reprint request] 100. Wagner, A. (2010) On the energy and material cost of gene duplication. In: Dittmar, K., Liberles, D. Evolution after gene duplication. Wiley-Blackwell, Hoboken, NJ, p 207-214. [reprint request] 99. Bragg, JG, Wagner, A. (2010) The evolution of protein material costs. In: Evolutionary genomics and systems biology, Caetano-Anolles, G., Ed., Wiley, NY, pp. 203-211. [reprint request] 2009 98. Bragg, J.G., Wagner, A. (2009) Protein material costs: single atoms can make an evolutionary difference. Trends in Genetics 25, 5-8. [reprint request] 97. Martin, O.C.M., Wagner, A. (2009) Effects of recombination on complex regulatory circuits. Genetics 183, 673-684. [reprint request] 96. Wagner, A. (2009) Evolutionary constraints permeate large metabolic networks. BMC Evolutionary Biology 9:231 [reprint request] 95. Rodrigues, J., Wagner, A. (2009) Evolutionary plasticity and innovations in complex metabolic reaction networks. PloS Computational Biology 5(12): e1000613. [reprint request] 94. Hafner, M., Koeppl, H., Hasler, M., Wagner, A. (2009) “Glocal” robustness analysis and model discrimination for circadian oscillators. PloS Computational Biology 5(10): e1000534. [reprint request] 93. de la Chaux, N., Wagner, A. (2009) Evolutionary dynamics of the LTR retrotransposon roo inferred from twelve complete Drosophila genomes. BMC Evolutionary Biology 9:205. [reprint request] 92. Wagner, A. (2009) Transposable elements as genomic diseases. Molecular Biosystems, 5 32. [reprint request] 91. Wagner, A. (2009) Networks in molecular evolution. In: Meyers, R.A. (ed.) Encyclopedia of Complexity and System Science. Springer, Heidelberg. [reprint request] 90. Hafner, M., Koeppl, H., Wagner, A. (2009) Evolution of feedback loops in oscillatory systems. Proceedings of the Third International Conference on Foundations of Systems Biology in Engineering (FOSBE 2009), Denver, CO, August 9-12, 2009. [reprint request] Hafner et al. 2009 2008 89. Wagner, A. (2008) Neutralism and selectionism: A network-based reconciliation. Nature Reviews Genetics 9, 965-974. [reprint request] 88. Wagner, A. (2008) Robustness and evolvability: A paradox resolved. Proc. Roy. Soc. London Series. B 275, 91-100. [reprint request] 87. Ferrada, E., Wagner, A. (2008) Protein robustness promotes evolutionary innovations on large evolutionary time scales Proc. Roy. Soc. London Series. B 275:1595-602. [reprint request] 86. Wright, J., Wagner, A. (2008) The systems biology research tool: Evolvable open-source software. BMC Systems Biology 2:55. [request reprint] 85. Martin, OC, Wagner, A. (2008) Multifunctionality and robustness tradeoffs in model genetic circuits. Biophysical Journal 94, 2927-2937. [request reprint] 84. Wagner, A. (2008) Gene duplications, robustness, and evolutionary innovations. Bioessays 30, 367-373. [reprint request] 83. Felix, M-A, Wagner, A. (2008) Robustness and evolution: concepts, insights, and challenges from a developmental model system. Heredity 100, 132-140. [reprint request] 82. Jörg, T., Martin, OC, Wagner, A. (2008) Neutral network sizes of biological RNA molecules can be computed and are atypically large. BMC Bioinformatics 9:464. [reprint request] 81. Wagner, A., de la Chaux, N. (2008) Distant horizontal gene transfer is rare for mobile prokaryotic DNA. Molecular Genetics and Genomics 280, 397-408. [reprint request] 80. Wright, J., Wagner, A. (2008) Exhaustive identification of steady state cycles in large stoichiometric networks. BMC Systems Biology, 2:61. [reprint request] 79. Fuller, M., Wagner, A. , Enquist, J. (2008) Using network analysis to characterize forest structure. Natural Resources Modeling 21, 225-247. [reprint request] 2007 78. Ciliberti, S., Martin, OC, Wagner, A. (2007) Innovation and robustness in complex regulatory gene networks. Proc. Natl. Acad. Sci. U.S.A. 104, 13591-13596. [reprint request] 77. Ciliberti, S, Martin, OC, Wagner, A. (2007) Robustness can evolve gradually in complex regulatory networks with varying topology. PLoS Computational Biology 3(2): e15. [reprint request] 76. Wagner, A., Lewis, C., Bichsel, M. (2007) A survey of transposable elements using IScan. Nucleic Acids Research 35, 5284-5293. [reprint request] 75. Wagner, A. (2007) Rapid detection of positive selection in genes and genomes through variation clusters. Genetics 176: 2451–2463. [reprint request] 74. Bragg, JG, Wagner, A. (2007) Protein carbon content evolves in response to carbon availability and may influence the fate of duplicated genes. Proc. Roy. Soc. London Series. B 274, 1063-1070. [reprint request] 73. Wagner, A. (2007) From bit to it: The transformation of information into living matter by metabolic networks. BMC Systems Biology 1: 33. [reprint request] 72. Wagner, A. (2007) Energy costs constrain the evolution of gene expression. Journal of Experimental Zoology (Molecular and Developmental Evolution) 308B:322–324 [reprint request] 71. Wagner, A., Wright, J. (2007) Alternative routes and mutational robustness in complex regulatory networks. Biosystems 88, 163-172. [reprint request] 70. Wagner, A. (2007) Gene networks and natural selection: Is there a network biology? In Pagel, M. Pomiankowski, A. (eds.) Evolutionary Genomics and Proteomics, Sinauer Associates, Sunderland, MA, USA. [Abstract] 69. Sumedha, Martin, OC, Wagner, A. (2007) New structural variation in evolutionary searches of RNA neutral networks. Biosystems 90: 475-485.
More here Just because he hasn't published in vanity ID journals doesn't mean he doesn't know what he is talking about :-)Me_Think
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