This parody of evo devo makes it sound a lot like ID

_{News
December 19, 2017

Cell biology, Evolution, Evolutionary biology

1}_{Categories
Cell biology
Evolution
Evolutionary biology}

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“This is how we go from single cells to people.” Hmmm.

See also: From Biology Direct: Darwinism, now thoroughly detached from its historical roots as a falsifiable theory, “must be abandoned”

Comments

DiEb: "gpucchio: what a pity – it seems that our areas of expertise do not overlap very much. I will follow your discussions with interest, but I doubt that I will contribute very much!" No problems! I appreciate your interest just the same. :)gpuccio_{January 22, 2018
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Dionisio, many really important domains defy precising definition. For instance, define biological life. We need not go beyond that to the soul. In many cases we are left to making a family resemblance case by case comparison between examples and counter-examples, an extended ostensive definition that guides conception that we have yet to be able to reduce to an exact statement of necessary and sufficient conditions or else genus and difference. Where Math comes in, we may be able to come up with models and structure relationships so that logic of structure and quantity applies. Sometimes we don't get that far. And in this case we are using ideas long familiar from statistical thermodynamics. And beyond: searching for a needle in a haystack is proverbial. KFkairosfocus_{January 22, 2018
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DiEb, FYI -since apparently you haven't noticed it yet- gpuccio's name does not have any letter 'h'. No idea where you got that from, but you wrote it incorrectly more than once. Please, show that you are indeed a mathematician and pay attention to details. At least to the important ones. A person's name is very important.Dionisio_{January 22, 2018
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KF @193:
definitionitis is an old complaint and too often a disease of the hyperskeptic that makes a mountain out of a mole-hill.
Very interesting description of an old problem. Perhaps this also applies to the still unsettled issues with terms like "evolution", "macroevolution", "microevolution"?Dionisio_{January 22, 2018
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DiEB:
KF, you obviously have no idea how modern mathematics work.
kairosfocus must be devastated by such a cunning and indepth argument. You really showed him, DiEB. :roll:ET_{January 22, 2018
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DiEb, really. There is a subject of interest that happens to be connected to the way statistical thermodynamics works. In that context, we can explore cut-down phase spaces (configuration spaces) and see what search challenge implies. The implication is plain, and it shows a good reason why inferring intelligently directed configuration on observing FSCO/I is reasonable. KF PS: Here are Davies and Walker, in a very similar vein:
In physics, particularly in statistical mechanics, we base many of our calculations on the assumption of metric transitivity, which asserts that a system’s trajectory will eventually [--> given "enough time and search resources"] explore the entirety of its state space – thus everything that is phys-ically possible will eventually happen. It should then be trivially true that one could choose an arbitrary “final state” (e.g., a living organism) and “explain” it by evolving the system backwards in time choosing an appropriate state at some ’start’ time t_0 (fine-tuning the initial state). In the case of a chaotic system the initial state must be specified to arbitrarily high precision. But this account amounts to no more than saying that the world is as it is because it was as it was, and our current narrative therefore scarcely constitutes an explanation in the true scientific sense. We are left in a bit of a conundrum with respect to the problem of specifying the initial conditions necessary to explain our world. A key point is that if we require specialness in our initial state (such that we observe the current state of the world and not any other state) metric transitivity cannot hold true, as it blurs any dependency on initial conditions – that is, it makes little sense for us to single out any particular state as special by calling it the ’initial’ state. If we instead relax the assumption of metric transitivity (which seems more realistic for many real world physical systems – including life), then our phase space will consist of isolated pocket regions and it is not necessarily possible to get to any other physically possible state (see e.g. Fig. 1 for a cellular automata example).
[--> or, there may not be "enough" time and/or resources for the relevant exploration, i.e. we see the 500 - 1,000 bit complexity threshold at work vs 10^57 - 10^80 atoms with fast rxn rates at about 10^-13 to 10^-15 s leading to inability to explore more than a vanishingly small fraction on the gamut of Sol system or observed cosmos . . . the only actually, credibly observed cosmos]
Thus the initial state must be tuned to be in the region of phase space in which we find ourselves [--> notice, fine tuning], and there are regions of the configuration space our physical universe would be excluded from accessing, even if those states may be equally consistent and permissible under the microscopic laws of physics (starting from a different initial state). Thus according to the standard picture, we require special initial conditions to explain the complexity of the world, but also have a sense that we should not be on a particularly special trajectory to get here (or anywhere else) as it would be a sign of fine–tuning of the initial conditions. [ --> notice, the "loading"] Stated most simply, a potential problem with the way we currently formulate physics is that you can’t necessarily get everywhere from anywhere (see Walker [31] for discussion). ["The “Hard Problem” of Life," June 23, 2016, a discussion by Sara Imari Walker and Paul C.W. Davies at Arxiv.]
kairosfocus_{January 22, 2018
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gpucchio: what a pity - it seems that our areas of expertise do not overlap very much. I will follow your discussions with interest, but I doubt that I will contribute very much!DiEb_{January 22, 2018
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KF, you obviously have no idea how modern mathematics work.DiEb_{January 22, 2018
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gpuccio @192:
"I am more than satisfied to demonstrate the empirical truth of the statement, in a specific context (biological systems)." "The concept of functional information greatly simplifies the approach to biological systems, and does not require a general theory of information or specification. It is a simple and powerful tool, perfectly appropriate for empirical design inference." "Empirical ID is, IMO, a very strong tool to demonstrate beyond any doubt the essential role of consciousness in generating complex functional information, and therefore the essential role of consciousness in reality."
I'm not a mathematician either, hence I like empirical evidences -specially in biology. The topic of complex functionally specified information associated with proteins and the interesting quantification approach you have described so extensively in several threads, are clear illustrations of the power of empirical demonstrations in biology.Dionisio_{January 22, 2018
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DiEb, definitionitis is an old complaint and too often a disease of the hyperskeptic that makes a mountain out of a mole-hill. In the context, we have dealt with configuration spaces, which can be regarded as phase spaces in which momentum issues are not material. In such spaces, we can see complexity through combinatorial explosion, e.g. for text strings. Since such strings can be used to describe a 3-d entity or a process etc, discussion on strings is WLOG. Now, certain clusters of configs in the space of possibilities w [for omega the traditional symbol in stat thermo-d] may be observably and identifiably distinct e.g. by providing some structurally based function, such as the correctly assembled parts of a 6500 c3 fishing reel, my favourite case. Thus we have a cluster of states that are functional in some way and a vastly larger number of clumped or scattered states that will not function in any relevant way. Of course the issue that relevant systems are self replicating is trotted out. the problem is we are looking at a cell-scale von Neuman kinematic self replicator, which is a further example of functionally specific complex orgtanisation and associated information that needs to be explained before it is allowed to drive all sorts of conclusions. Yes, OOL must be solved first. We then can ask ourselves, how do we get to such a cluster or island of function, a case e from a zone E within w. If by blind chance and/or mechanical necessity, any reasonable assignment of probabilities of accessing cases c for a complex case such that c is in E, will be rapidly negligibly different from zero. Exponential explosion of possibilities as n bits have 2^n possible configs. More complex cases can be reduced to bits. This of course runs into challenges of numerically or algebraically defining probabilities and defining functional targets. There is an answer: search challenge. Long since put here at UD and elsewhere. Once the space w is for at least 500 - 1,000 bits, we are looking at 3.27*10^150 - 1.07*10^301 possibilities. The atomic resources and atomic interaction rates for the 10^57 atoms of the sol system for the low end and the 10^80 for the observed cosmos at the high end, are such that the fraction of selected possibilities c from w is negligibly different from 0. So, it is maximally implausible to reach any reasonably isolated island of function in the space by blind search. Plausibility fail, backed up by utter want of empirical observation. And, search then is implied as sampling of subsets in config spaces relevant to our studies. Here, as default, blindly by chance and mechanical necessity. Try AA sequence space and codon space that targets it. We could try random bit strings for AUTOCAD, hoping to come up with a design for a reel, or we can try random ASCII text to get text from the corpus of literature in English or the like. All these cases give the same result, for rather obvious reasons. Likewise, we can then say oh we have some circumstance that searches are very effective as natural selection is held to be. Of course that is within islands of function, when we need to find the islands as the first problem, not incremental hill climbing within the island. In any case as searches are effectively subsets, they come from the power set of the space and so are exponentially harder, space of size w has power set of size 2^w. Search for golden search is far worse than direct search per whatever atomic level interactions occur in sol system or observed cosmos. Such cases of functionally specific complex organisation and associated information have just one well known causal source: intelligently directed configuration. But the whole point is, after years and years you and others of like ilk still want to sweep that inconvenient fact off the board and so repeatedly rhetorically pretend we have not provided a serious answer. It has been there, for decades. KFkairosfocus_{January 22, 2018
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DiEb: "I could agree with such a definition" I suppose that's enough form me. :) "BTW: my definition of a search is quite straight-forward: find the alpha in a space Omega where a given function f: Omega -> R takes its optimum. (R should be suitable…) This definition seems to work for all examples in DEM’s textbook…." I am not a mathematician, but your definition seems fine, as far as I can say. I can certainly agree with you on one point: it is very important to have explicit and clear definitions of the things we debate. That's why I have started my OPs here, some time ago, by giving my personal and explicit definitions of design and of complex functional information: https://uncommondescent.com/intelligent-design/defining-design/ https://uncommondescent.com/intelligent-design/functional-information-defined/ I cannot really follow the theoretical and mathematical problems that arise in the specific tasks that Dembski and Marks are pursuing. I am not a mathematician. I understand that they are trying to prove mathematically that complex specified information cannot arise in any possible system. I believe that they are right, essentially, but I cannot judge if they have succeeded in demonstrating that point rigorously. I am more than satisfied to demonstrate the empirical truth of the statement, in a specific context (biological systems). For example, I must confess that I have always had problems with Dembski's paper about specification: https://billdembski.com/documents/2005.06.Specification.pdf Many times, in the discussions here, I have been invited to defend it, but I cannot do that, because I certainly don't understand it, so usually I suspend any judgement about it. For my reasonings, I have always used, very simply, the concept of functional specification, which can be objectively defined and applied: https://uncommondescent.com/intelligent-design/functional-information-defined/ The concept of functional information greatly simplifies the approach to biological systems, and does not require a general theory of information or specification. It is a simple and powerful tool, perfectly approrpiate for empirical design inference. I am not really sure that specification can be universally defined without making any reference to conscious agents, because it arises in consciousness, and it requires consciousness to be defined and detected. Using a conscious agent to define "any possible function", as I do in my definition of functional information, does not make the functional specification in any way subjective. It reamins a very objective property, which can be objectively assessed in real systems. I am very intrigued by the concept of conservation of information. Intuitively, I believe that it is true. But probably it is very difficult to define it mathematically. So, I hope that Dembski and Marks may have the greatest success in their research, but I am not the best person to judge it in detail. Empirical ID is, IMO, a very strong tool to demonstrate beyond any doubt the essential role of consiousness in generating complex functional information, and therefore the essential roole of consciousness in reality.gpuccio_{January 22, 2018
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Private debate? Your email would just ask what they meant by the word "search". And if they don't respond then just use the standard dictionary definitions. The context would determine which definition is being used.ET_{January 22, 2018
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Has DiEB ever just bothered to ask Dembski, Marks or Ewert what the meant or if they are using the word differently than standardly defined?
There is no forum for such questions - even when Dr. Dembski was on the helm of this blog, he didn't engage his critics were often. The authors often ignore emails: Dr. Marks once said that he would not engage in private debate with those who are publicly critical to his position... IIRC, the last time critics had an opportunity to ask questions of one of the authors of "Introduction to Evolutionary Informatics" was in 2015 on UD: Dr. Ewert Answers. Unfortunately, Dr. Ewert did not accept any follow-up questions, so the whole exercise was somewhat futile...DiEb_{January 22, 2018
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Evolution by means of blind and mindless processes isn't a search. It isn't a creative force, either. Has DiEB ever just bothered to ask Dembski, Marks or Ewert what the meant or if they are using the word differently than standardly defined?ET_{January 22, 2018
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BTW: my definition of a search is quite straight-forward: find the alpha in a space Omega where a given function f: Omega -> R takes its optimum. (R should be suitable...) This definition seems to work for all examples in DEM's textbook....DiEb_{January 22, 2018
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gpucchio @186:
Can you agree with this kind of definition of “search” (or any other way we can agree to call it)?
I could agree with such a definition, but I'm afraid that Dembski, Marks, and Ewert could not. For their ideas in "A Search for a Search" (S4S) and subsequent papers, they need a definition which allows to identify a search with a probability measure (S4S) or at least to be represented by a p.m. (as in their article "A General Theory of Information Cost Incurred by Successful Search" in "Biological Information - New Perspectives") I found both of these definitions troubling: in S4S, the space on which they defined their measure (the set of all queries of a certain length) wasn't a measurable space in any sensible way, while the other definition implied that all complete searches work on average only as well as a single random guess. In "Introduction to Evolutionary Informatics", they use the term search quite a lot, but without defining it properly - at least I haven't found the definition yet, perhaps another reader can show it to me? They just state that
We note, however, the choice of an algorithm along with its parameters and initialization imposes a probability distribution over the search space. (p. 173)
That's a bold statement - and as far as I can see, it is just wrong.DiEb_{January 22, 2018
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Lots of “where’s the beef?” questions for the referenced papers. Lots of "parole, parole, parole" in the referenced papers.Dionisio_{January 22, 2018
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F-box proteins are substrate adaptors used by the SKP1-CUL1-F-box protein (SCF) complex, a type of E3 ubiquitin ligase complex in the ubiquitin proteasome system (UPS). SCF-mediated ubiquitylation regulates proteolysis of hundreds of cellular proteins involved in key signaling and disease systems. However, our knowledge of the evolution of the F-box gene family in Euarchontoglires is limited. In the present study, 559 F-box genes and nine related pseudogenes were identified in eight genomes. Lineage-specific gene gain and loss events occurred during the evolution of Euarchontoglires, resulting in varying F-box gene numbers ranging from 66 to 81 among the eight species. Both tandem duplication and retrotransposition were found to have contributed to the increase of F-box gene number, whereas mutation in the F-box domain was the main mechanism responsible for reduction in the number of F-box genes, resulting in a balance of expansion and contraction in the F-box gene family. Thus, the Euarchontoglire F-box gene family evolved under a birth-and-death model. Signatures of positive selection were detected in substrate-recognizing domains of multiple F-box proteins, and adaptive changes played a role in evolution of the Euarchontoglire F-box gene family. In addition, single nucleotide polymorphism (SNP) distributions were found to be highly non-random among different regions of F-box genes in 1092 human individuals, with domain regions having a significantly lower number of non-synonymous SNPs. Wang, Ailan & Fu, Mingchuan & Jiang, Xiaoqian & Y.H., Mao & Li, Xiangchen & Tao, Shiheng. (2014). Evolution of the F-Box Gene Family in Euarchontoglires: Gene Number Variation and Selection Patterns. PloS one. 9. e94899. 10.1371/journal.pone.0094899.Dionisio_{January 22, 2018
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Thermodynamic stability, as expressed by the Second Law, generally constitutes the driving force for chemical assembly processes. Yet, somehow, within the living world most self-organisation processes appear to challenge this fundamental rule. Even though the Second Law remains an inescapable constraint, under energy-fuelled, far-from-equilibrium conditions, populations of chemical systems capable of exponential growth can manifest another kind of stability, dynamic kinetic stability (DKS). It is this stability kind based on time/persistence, rather than on free energy, that offers a basis for understanding the evolutionary process. Furthermore, a threshold distance from equilibrium, leading to irreversibility in the reproduction cycle, is needed to switch the directive for evolution from thermodynamic to DKS. The present report develops these lines of thought and argues against the validity of a thermodynamic approach in which the maximisation of the rate of energy dissipation/entropy production is considered to direct the evolutionary process. More generally, our analysis reaffirms the predominant role of kinetics in the self-organisation of life, which, in turn, allows an assessment of semi-quantitative constraints on systems and environments from which life could evolve. Pross, Addy & Pascal, Robert. (2017). How and why kinetics, thermodynamics, and chemistry induce the logic of biological evolution. Beilstein Journal of Organic Chemistry. 13. 665-674. 10.3762/bjoc.13.66. http://www.beilstein-journals.org/bjoc/content/supplementary/1860-5397-13-66-S1.pdfDionisio_{January 22, 2018
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Mateus, Marcos. (2017). Milking spherical cows—Yet another facet of model complexity. Ecological Modelling. 354. . 10.1016/j.ecolmodel.2017.03.001. download here: https://authors.elsevier.com/a/1Us-X15DJ~pjN7Dionisio_{January 22, 2018
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A significant number of synthetic systems capable of replicating themselves or entities that are complementary to themselves have appeared in the last 30 years. Building on an understanding of the operation of synthetic replicators in isolation, this field has progressed to examples where catalytic relationships between replicators within the same network and the extant reaction conditions play a role in driving phenomena at the level of the whole system. Systems chemistry has played a pivotal role in the attempts to understand the origin of biological complexity by exploiting the power of synthetic chemistry, in conjunction with the molecular recognition toolkit pioneered by the field of supramolecular chemistry, thereby permitting the bottom-up engineering of increasingly complex reaction networks from simple building blocks. This review describes the advances facilitated by the systems chemistry approach in relating the expression of complex and emergent behaviour in networks of replicators with the connectivity and catalytic relationships inherent within them. These systems, examined within well-stirred batch reactors, represent conceptual and practical frameworks that can then be translated to conditions that permit replicating systems to overcome the fundamental limits imposed on selection processes in networks operating under closed conditions. This shift away from traditional spatially homogeneous reactors towards dynamic and non-equilibrium conditions, such as those provided by reaction–diffusion reaction formats, constitutes a key change that mimics environments within cellular systems, which possess obvious compartmentalisation and inhomogeneity. Kosikova, Tamara & Philp, Douglas. (2017). Exploring the emergence of complexity using synthetic replicators. Chemical Society Reviews. 46. . 10.1039/C7CS00123A.Dionisio_{January 22, 2018
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Lots of "where's the beef?" questions for the referenced papers.Dionisio_{January 22, 2018
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The creation of reaction networks capable of exhibiting responses that are properties of entire systems represents a significant challenge for the chemical sciences. The system-level behavior of a reaction network is linked intrinsically to its topology and the functional connections between its nodes. A simple network of chemical reactions constructed from four reagents, in which each reagent reacts with exactly two others, can exhibit upregulation of two products even when only a single chemical reaction is addressed catalytically. We implement a system with this topology using two maleimides and two nitrones of different sizes—either short or long and each bearing complementary recognition sites—that react pairwise through 1,3-dipolar cycloaddition reactions to create a network of four length-segregated replicating templates. Comprehensive 1H NMR spectroscopy experiments unravel the network topology, confirming that, in isolation, three out of four templates self-replicate, with the shortest template exhibiting the highest efficiency. The strongest template effects within the network are the mutually crosscatalytic relationships between the two templates of intermediate size. The network topology is such that the addition of different preformed templates as instructions to a mixture of all starting materials elicits system-level behavior. Instruction with a single template up-regulates the formation of two templates in a predictable manner. These results demonstrate that the rules governing system-level behavior can be unraveled through the application of wholly synthetic networks with well-defined chemistries and interactions. Sadownik, Jan & Kosikova, Tamara & Philp, Douglas. (2017). Generating System-Level Responses from a Network of Simple Synthetic Replicators. Journal of the American Chemical Society. 139. . 10.1021/jacs.7b09735.Dionisio_{January 22, 2018
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As a step towards understanding pre-evolutionary organization in non-genetic systems, we develop a model to investigate the emergence and dynamics of proto-autopoietic networks in an interacting population of simple information processing entities (automata). These findings may be relevant to understanding how inanimate systems such as chemically communicating protocells can initiate the transition to living matter prior to the onset of contemporary evolutionary and genetic mechanisms. Emergence and dynamics of self-producing information niches as a step towards pre-evolutionary organization Richard J. Carter, Karoline Wiesner, Stephen Mann DOI: 10.1098/rsif.2017.0807 Journal of the Royal Society Interface http://rsif.royalsocietypublishing.org/content/15/138/20170807Dionisio_{January 22, 2018
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Large facilities and the evolving ribosome, the cellular machine for genetic-code translation Ada Yonath DOI: 10.1098/rsif.2009.0167.focus Journal of the Royal Society InterfaceDionisio_{January 22, 2018
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R-ChIP Using Inactive RNase H Reveals Dynamic Coupling of R-loops with Transcriptional Pausing at Gene Promoters http://www.sciencedirect.com/science/article/pii/S1097276517307578Dionisio_{January 21, 2018
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gooshy, If I got your joke right, the mainstream media can turn anyone into a celebrity if they want to. Celebrities are objects they promote for profitable sale. What made you write in this thread? I'm just curious. Thanks.Dionisio_{January 21, 2018
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Dionisio @159, yes it was. Just a little levity.gooshy_{January 21, 2018
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Genitalia are among the most studied phenotypes because they exhibit high anatomical diversity, experience fast evolutionary rates and may be shaped by several evolutionary mechanisms. A key element to uncover the mechanisms behind such impressive diversity is their copulatory function. This topic has been overlooked, especially concerning structures not directly involved in sperm transfer and reception. Here, we conduct a hypothesis-driven experimental study to elucidate the operation of various external genital parts in five species of stink bugs with differing levels of phylogenetic relatedness. These insects are unique because their male and female genitalia are externally well developed, rigid and composed of multiple components. In contrast with their anatomical complexity and diversity, we show that genital structures work jointly to perform a single function of mechanical stabilization during copula. However, distinct lineages have evolved alternative strategies to clasp different parts of the opposite sex. In spite of a high functional correspondence between male and female traits, the overall pattern of our data does not clearly support an intersexual coevolutionary scenario. We propose that the extraordinary male genital diversity in the family is probably a result of a process of natural selection enhancing morphological accommodation, but we consider alternative mechanisms. Genevcius, Bruno. (2017). Strong functional integration among multiple parts of the complex male and female genitalia of stink bugs. Biological Journal of the Linnean Society. 1-13. 10.1093/biolinnean/blx095. https://www.researchgate.net/profile/Bruno_Genevcius/publication/320615982_Strong_functional_integration_among_multiple_parts_of_the_complex_male_and_female_genitalia_of_stink_bugs/links/59f09dbfaca272cdc7cde80c/Strong-functional-integration-among-multiple-parts-of-the-complex-male-and-female-genitalia-of-stink-bugs.pdfDionisio_{January 21, 2018
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Despite claims that genitalia are among the fastest evolving phenotypes, few studies have tested this trend in a quantitative and phylogenetic framework. In systems where male and female genitalia coevolve, there is a growing effort to explore qualitative patterns of evolution and their underlying mechanisms, but the temporal aspect remains overlooked. An intriguing question is how fast male and female genitalia may change in a coevolutionary scenario. Here we apply a series of comparative phylogenetic analyses to reveal a scenario of correlated evolution and to investigate how fast male and female external, non-homologous and functionally integrated genitalia change in a group of stink bugs. We report three findings: the female gonocoxite 8 and the male pygophore showed a clear pattern of correlated evolution, both genitalia were estimated to evolve much faster than non-genital traits, and rates of evolution of the male genitalia were twice as fast as the female genitalia. Our results corroborate the widely held view that male genitalia evolve fast and add to the scarce evidence for rapidly evolving female genitalia. Different rates of evolution exhibited by males and females suggest either distinct forms or strengths of selection, despite their tight functional integration and coevolution. The morphological characteristic of this coevolutionary trend are more consistent with a cooperative adjustment of the genitalia, suggesting a scenario of female choice, morphological accommodation, lock-and-key or some combination of the three This article is protected by copyright. All rights reserved. Genevcius, Bruno & Caetano, Daniel & Schwertner, Cristiano. (2016). Rapid differentiation and asynchronous coevolution of male and female genitalia in stink bugs. Journal of evolutionary biology. 30. . 10.1111/jeb.13026. https://www.researchgate.net/profile/Bruno_Genevcius/publication/311704430_Rapid_differentiation_and_asynchronous_coevolution_of_male_and_female_genitalia_in_stink_bugs/links/58bf013a92851cd83aa1253b/Rapid-differentiation-and-asynchronous-coevolution-of-male-and-female-genitalia-in-stink-bugs.pdfDionisio_{January 21, 2018
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