New Paper Demonstrates Superiority of Design Model

Ten Thousand Bits?

Did you know Mars is going backwards? For the past few weeks, and for several weeks to come, Mars is in its retrograde motion phase. If you chart its position each night against the background stars, you will see it pause, reverse direction, pause again, and then get going again in its normal direction. And did you further know that retrograde motion helped to cause a revolution? Two millennia ago, Aristotelian physics dictated that the Earth was at the center of the universe. Aristarchus’ heliocentric model, which put the Sun at the center, fell out of favor. But what Aristotle’s geocentrism failed to explain was retrograde motion. If the planets are revolving about the Earth, then why do they sometimes pause, and reverse direction? That problem fell to Ptolemy, and the lessons learned are still important today.

Ptolemy explained anomalies such as retrograde motion with additional mechanisms, such as epicycles, while maintaining the circular motion that, as everyone knew, must be the basis of all motion in the cosmos. With less than a hundred epicycles, he was able to model, and predict accurately the motions of the cosmos. But that accuracy came at a cost—a highly complicated model.

In the Middle Ages William of Occam pointed out that scientific theories ought to strive for simplicity, or parsimony. This may have been one of the factors that drove Copernicus to resurrect Aristarchus’ heliocentric model. Copernicus preserved the required circular motion, but by switching to a sun-centered model, he was able to reduce greatly the number of additional mechanisms, such as epicycles.

Both Ptolemy’s and Copernicus’ models accurately forecast celestial motion. But Copernicus was more parsimonious. A better model had been found.

Kepler proposed ellipses, and showed that the heliocentric model could become even simpler. It was not well accepted though because, as everyone knew, celestial bodies travel in circles. How foolish to think they would travel along elliptical paths. That next step toward greater parsimony would have to wait for the likes of Newton, who showed that Kepler’s ellipses were dictated by his new, highly parsimonious, physics. Newton described a simple, universal, gravitational law. Newton’s gravitational force would produce an acceleration, which could maintain orbital motion in the cosmos.

But was there really a gravitational force? It was proportional to the mass of the object which was then cancelled out to compute the acceleration. Why not have gravity cause an acceleration straightaway?

Centuries later Einstein reported on a man in Berlin who fell out of a window. The man didn’t feel anything until he hit the ground! Einstein removed the gravitational force and made the physics even simpler yet.

The point here is that the accuracy of a scientific theory, by itself, means very little. It must be considered along with parsimony. This lesson is important today in this age of Big Data. Analysts know that a model can always be made more accurate by adding more terms. But are those additional terms meaningful, or are they merely epicycles? It looks good to drive the modeling error down to zero by adding terms, but when used to make future forecasts, such models perform worse.

There is a very real penalty for adding terms and violating Occam’s Razor, and today advanced algorithms are available for weighing the tradeoff between model accuracy and model parsimony.

This brings us to common descent, a popular theory for modeling relationships between the species. As we have discussed many times here, common descent fails to model the species, and a great many additional mechanisms—biological epicycles—are required to fit the data.

And just as cosmology has seen a stream of ever improving models, the biological models can also improve. This week a very important model has been proposed in a new paper, authored by Winston Ewert, in the Bio-Complexity journal.

Inspired by computer software, Ewert’s approach models the species as sharing modules which are related by a dependency graph. This useful model in computer science also works well in modeling the species. To evaluate this hypothesis, Ewert uses three types of data, and evaluates how probable they are (accounting for parsimony as well as fit accuracy) using three models.

Ewert’s three types of data are: (i) Sample computer software, (ii) simulated species data generated from evolutionary / common descent computer algorithms, and (iii) actual, real species data.

Ewert’s three models are: (i) A null model in which entails no relationships between
any species, (ii) an evolutionary / common descent model, and (iii) a dependency graph model.

Ewert’s results are a Copernican Revolution moment. First, for the sample computer software data, not surprisingly the null model performed poorly. Computer software is highly organized, and there are relationships between different computer programs, and how they draw from foundational software libraries. But comparing the common descent and dependency graph models, the latter performs far better at modeling the software “species.” In other words, the design and development of computer software is far better described and modeled by a dependency graph than by a common descent tree.

Second, for the simulated species data generated with a common descent algorithm, it is not surprising that the common descent model was far superior to the dependency graph. That would be true by definition, and serves to validate Ewert’s approach. Common descent is the best model for the data generated by a common descent process.

Third, for the actual, real species data, the dependency graph model is astronomically superior compared to the common descent model.

Let me repeat that in case the point did not sink in. Where it counted, common descent failed compared to the dependency graph model. The other data types served as useful checks, but for the data that mattered—the actual, real, biological species data—the results were unambiguous.

Ewert amassed a total of nine massive genetic databases. In every single one, without exception, the dependency graph model surpassed common descent.

Darwin could never have even dreamt of a test on such a massive scale.

Darwin also could never have dreamt of the sheer magnitude of the failure of his theory. Because you see, Ewert’s results do not reveal two competitive models with one model edging out the other.

We are not talking about a few decimal points difference. For one of the data sets (HomoloGene), the dependency graph model was superior to common descent by a factor of 10,064. The comparison of the two models yielded a preference for the dependency graph model of greater than ten thousand.

Ten thousand is a big number.

But it gets worse, much worse.

Ewert used Bayesian model selection which compares the probability of the data set given the hypothetical models. In other words, given the model (dependency graph or common descent), what is the probability of this particular data set? Bayesian model selection compares the two models by dividing these two conditional probabilities. The so-called Bayes factor is the quotient yielded by this division.

The problem is that the common descent model is so incredibly inferior to the dependency graph model that the Bayes factor cannot be typed out. In other words, the probability of the data set given the dependency graph model, is so much greater than the probability of the data set given the common descent model, that we cannot type the quotient of their division.

Instead, Ewert reports the logarithm of the number. Remember logarithms? Remember how 2 really means 100, 3 means 1,000, and so forth?

Unbelievably, the 10,064 value is the logarithm (base value of 2) of the quotient! In other words, the probability of the data on the dependency graph model is so much greater than that given the common descent model, we need logarithms even to type it out. If you tried to type out the plain number, you would have to type a 1 followed by more than 3,000 zeros!

That’s the ratio of how probable the data are on these two models!

By using a base value of 2 in the logarithm we express the Bayes factor in bits. So the conditional probability for the dependency graph model has a 10,064 advantage of that of common descent.

10,064 bits is far, far from the range in which one might actually consider the lesser model. See, for example, the Bayes factor Wikipedia page, which explains that a Bayes factor of 3.3 bits provides “substantial” evidence for a model, 5.0 bits provides “strong” evidence, and 6.6 bits provides “decisive” evidence.

This is ridiculous. 6.6 bits is considered to provide “decisive” evidence, and when the dependency graph model case is compared to comment descent case, we get 10,064 bits.

But it gets worse.

The problem with all of this is that the Bayes factor of 10,064 bits for the HomoloGene data set is the very best case for common descent. For the other eight data sets, the Bayes factors range from 40,967 to 515,450.

In other words, while 6.6 bits would be considered to provide “decisive” evidence for the dependency graph model, the actual, real, biological data provide Bayes factors of 10,064 on up to 515,450.

We have known for a long time that common descent has failed hard. In Ewert’s new paper, we now have detailed, quantitative results demonstrating this. And Ewert provides a new model, with a far superior fit to the data.

Here’s That Algae Study That Decouples Phylogeny and Competition

“We Were Completely Baffled”

In Charles Darwin’s theory of evolution the engine of progress is death. Nature is one big Malthusian battlefield as natural selection kills off the less-fit designs. As David Hume had put it a century before, “A perpetual war is kindled amongst all living creatures,” and nature is so arranged so as “to embitter the life of every living being.” In Darwin’s day Alfred, Lord Tennyson found that nature was “red in tooth and claw” and Herbert Spencer summarized Darwin’s new theory as the “Survival of the Fittest.” Or as Nietzsche lamented, it is the weak “who most undermine life.” But there’s only one problem: this is all the result of junk science. For every Serengeti Plain there are untold stories of mutualism and cooperation between species which contradict one of evolution’s most fundamental predictions. All of this came to light once again in a massive evolutionary study of algae.

In the algae study the researchers competed various pairs of freshwater green algae species against each other. Those species that are thought to be more closely related in the evolutionary tree should have competed against each other more intensely. On the other hand, species that are farther apart in the evolutionary tree should exhibit less competition.

But none of this was found in the experimental results. No such trends were found and once again the theory of evolution produced a false prediction and did not help to explain the scientific evidence. The team spent months trying to resolve the problem, but to no avail. As one of the researchers explained:

It was completely unexpected. When we saw the results, we said ‘this can’t be.’ We sat there banging our heads against the wall. Darwin’s hypothesis has been with us for so long, how can it not be right? … When we started coming up with numbers that showed he [Darwin] wasn’t right, we were completely baffled. … We should be able to look at the Tree of Life, and evolution should make it clear who will win in competition and who will lose. But the traits that regulate competition can’t be predicted from the Tree of Life.

Of course none of this has anyone doubting the truth of evolution. It just must be more complicated than was previously thought. Perhaps algae are “plastic” and diverging in ways unrelated to competition. Or perhaps nature’s species cooperate at greater levels than was thought. Perhaps there is more co-evolution between species, resulting in more cooperation.

You see there are always more epicycles for evolution. With each new absurdity another new complicated just-so story is woven into evolutionary theory. As Lakatos explained, some theories simply are not falsifiable. But as a result they sacrifice realism and parsimony.

Religion drives science, and it matters.

A Clever Spliceosome Mechanism Was Just Reported

And a Massive Violation of Occam’s Razor

In the seventeenth century clocks were a favorite comparison with the complex workings of nature. In the eighteenth century the analogy switched to watches. Now, with the latest crystal structure mapping of the incredible spliceosome machine, which edits newly transcribed gene transcripts, we’re back to clocks. But this time the complexity services evolution rather than design. First for an explanation of the results:

A grandfather clock is, on its surface, a simple yet elegant machine. Tall and stately, its job is to steadily tick away the time. But a look inside reveals a much more intricate dance of parts, from precisely-fitted gears to cable-embraced pulleys and bobbing levers.

Like exploring the inner workings of a clock, a team of University of Wisconsin-Madison researchers is digging into the inner workings of the tiny cellular machines called spliceosomes, which help make all of the proteins our bodies need to function.

The spliceosome is truly an amazing molecular machine. In fact one of the new findings was a clever, unique interlocking mechanism between a protein and RNA in the spliceosome. And what does such complexity suggest to evolutionists?

Could this be a challenge for the theory that cannot even explain how a single protein could have evolved, let alone a massive molecular machine such as the spliceosome?

By no means. In fact, the evolutionists simply concluded that evolution must be even smarter than we thought it was. For such a clever mechanism must mean that protein and RNA have (somehow) evolved together in a much more coordinated fashion than was previously thought:

What's so cool is the degree of co-evolution of RNA and protein. It's obvious RNA and protein had to be pretty close friends already to evolve like this.

Funny how a contradiction is cool. In fact what is cool is the mechanism itself that was discovered. Its hypothetical evolution is what philosophers call a multiplied entity. Evolutionists are constantly adding their unnecessary explanatory mechanisms which add nothing to the science except an unlikely origins narrative.

Mechanisms such as these remind us that biology, like clocks, is full of parts that fit together. That means that both parts are required for the mechanism to work.

That easily contradicts evolution’s blind action, which can’t even reroute a nerve. How could it luckily evolve two parts together? What is needed is a gradual pathway of functional intermediates. Needless to say evolutionists know of no such pathway. That doesn’t mean it doesn’t exist, but it does raise the question of how evolutionists can be so certain that it exists. Particularly when evolution cannot even explain how a single protein could have evolved.

Religion drives science, and it matter.

Guess the Evidence for Early Evolution

A Complicated Narrative

As Aaron David Goldman summarized this month, the evolution of early life was a complicated affair. First of all there was the origin of life (OOL) events that produced the first living organism. Then there was a tremendous amount of evolutionary progress leading to the last universal common ancestor (LUCA) of today’s extant species. LUCA probably had DNA, an impermeable phospholipid membrane with much the same small army of proteins that attend to today’s cell membranes, the famed ATPase turbine-driven enzyme for ATP construction, protein synthesis machinery like today’s cells, the universal DNA code and DNA repair mechanisms. In short, LUCA was, as Goldman explains, a “sophisticated cellular organism that, if alive today, would probably be difficult to distinguish from other extant bacteria or archaea.”

Strangely enough DNA replication that we see in today’s cells was not present in LUCA. Instead RNA polymerases performed that job. Later in evolutionary history, today’s complex and circuitous DNA replication incredibly evolved independently several times. Also the aminoacyl tRNA synthetases underwent considerable horizontal gene transfer (HGT).

This is but a small sampling of the complicated evolutionary narrative of early life. And what exactly is the evidence for this Darwinian choreography leading from OOL to LUCA and finally to the three cell domains? Well actually there is, err, none.

In fact, not only is there no evidence for this narrative, evolutionists have repeatedly been stymied in their attempts to demonstrate how it would work in the laboratory. In fact, they can’t even demonstrate how it would work outside of the laboratory. Even when evolutionists are free to speculate and hypothesize with computer models or cartoon renditions, the problem still resists solution because it is too unlikely.

And so why do evolutionists believe all these things about early evolution? Because this circuitous narrative is required if evolution is true. In other words, the evidence for all these things is the fact of evolution. If the species spontaneously arose, as evolutionists insist is a fact, then this early life narrative, in one form or another must have occurred.

They are forced to believe that the OOL somehow occurred, in spite of the science. They are forced to believe that incredible complexity evolved early in evolutionary history because today’s extant species have too much in common. From an evolutionary perspective, those similarities must have been present in LUCA. Likewise DNA replication must not have been present in LUCA because the DNA replication machinery in today’s species reveals too many differences.

Furthermore the aminoacyl tRNA synthetases fail to form an evolutionary tree. So evolutionists must believe HGT caused the confusion. There is no independent evidence that HGT changed around the aminoacyl tRNA synthetases. The evidence simply is the failure to find an adequate evolutionary tree to explain these enzymes.

Similarly there is no evidence that today’s complex and circuitous DNA replication evolved independently several times. Again it is a result of believing in evolution. If the species spontaneously arose then, yes, DNA replication must have evolved independently several times.

Early evolution is an example of how evolution violates Occam’s Razor. Science seeks parsimonious solutions, but evolution leads to circuitous narratives. Religion drives science, and it matters.

We Have a Backup Sense of Smell to Protect the Lungs

Just Not That Smart

Our noses have specialized cells that give us a sense of the vapors around us by detecting the presence of chemicals and sending signals to the brain. New research is now explaining how our lungs also have such chemosensors. These sensors send signals not to the brain but to the nearby tissues causing a fast response, such as coughing and wheezing, when we inhale irritating or toxic vapors. Our lungs need this protection since they essentially are open to the external environment. As one evolutionist explained, “it makes sense that we evolved mechanisms to protect ourselves.” But such reasoning violates Occam’s Razor and reveals again how Aristotelianism lives on inside of evolution.

In science we must never multiply entities. That is, gratuitous explanations are not allowed. In this example of odor receptors in the lungs, there is no evidence that they evolved. Indeed, it is highly unlikely. We would have to believe that chance mutations caused odor receptors to be constructed at random locations around the body. And since these are chance mutations, we must also believe that other types of receptors would also be constructed. Furthermore, other types of cells (other than receptors) would be constructed. In short, a vast universe of possibilities would constantly be sampled by evolution. Light sensors, otherwise found in our eye, must have appeared on our big toe at some point in evolutionary history.

Evolution must have been sampling an astronomically large hyper-dimensional design space. Otherwise it never would have luckily constructed these odor receptors in our lungs.

But that is not all.

Having luckily constructed these odor receptors in our lungs (and in the right place in our lungs), there would have been precisely zero benefit. It would have made no difference because there would have been no signaling pathways, to the nearby tissues, for those receptors to excite. And those signaling pathways would have to, in turn, excite the correct type of response. It wouldn’t help much if the response, rather than coughing, would have been to breathe deeply.

With evolution we must believe that not only did it luckily construct the right kinds of receptors in the right place, but it also constructed the right kinds of signals and responses, so the entire system would work. Such an outcome is improbable.

So the evolution of these odor response systems in the lungs is not likely to have occurred. In fact, it is astronomically unlikely. It is not a scientifically motivated idea and it violates Occam’s Razor to say that “it makes sense that we evolved mechanisms to protect ourselves.” The correct scientific conclusion would be: “it makes sense that we have mechanisms to protect ourselves.”

And this leads us to another aspect of Aristotelianism within evolutionary thought.  Of course there is evolution’s incessant reliance on Aristotelianism’s teleological language. But there is also the use of explanations which, themselves, are in need of explaining. Saying that it “makes sense” that the lung’s odor response system evolved explains nothing and raises enormous questions about how that possibly could have evolved.

This is no different than Aristotelianism’s notorious “qualities” that Descartes bemoaned. A hot fire dried out a damp cloth because, Aristotelians explained, fire has the quality of dryness and heat. But these were nothing more than descriptive labels. The qualities did not explain how the fire dried the cloth. As Descartes later complained:

If you find it strange that … I do not use the qualities called “heat,” “cold,” “moistness,” and “dryness,” as do the philosophers, I shall say to you that these qualities appear to me to be themselves in need of explanation.

Likewise, if you find it strange that we do not use the mechanism called “evolution,” as do the philosophers, we shall say to you that this mechanism appears to us to be itself in need of explanation.

Nothing in biology makes sense in the light of evolution.

The Mystery of Extreme Non-Coding Conservation

No Plausible Speculations

Evolution is unique in that while it is well known amongst evolutionists to be a fact, its predictions often turn out false. Consider this new paper from the Royal Society on “The mystery of extreme non-coding conservation” that has been found across many genomes. Years ago an evolution professor told me, in defending the claim that evolution is falsifiable, that if functionally unconstrained yet highly similar DNA sequences were found in different species, then evolution would be false. A few years later that is exactly what was discovered. In fact, the DNA sequences were extremely similar and even identical in different species, and when they were altogether removed from mice it made no detectable difference. Hundreds of tests showed no significant difference between mice with and without long stretches of these DNA sequences. Did the professor agree that evolution was false? Not at all. For the fact of evolution goes far deeper than scientific findings and failed predictions. Nonetheless, ten years later, the mystery of extreme DNA conservation remains.

As the paper explains, there is currently “no known mechanism or function that would account for this level of conservation at the observed evolutionary distances.” This failure forces us to draw upon the typical explanatory mechanisms. The evolution of these extremely conserved sequences must have been abrupt and rapid, occurring in “short bursts.”

And since some of these sequences are found across a wide range of different species, the sequences, and whatever selective forces preserved them, must have been present very early in evolutionary history. On the other hand many of these sequences point to evolution’s nemesis, lineage-specific biology.

Some of these sequences are extremely conserved within lineages, but not across lineages. This forces us to conclude that the ancestral sequence first somehow arose in the common ancestor, later evolved independently in the different lineages which arose, became completely different in those different lineages, and then finally each of these different sequences, in the respective lineages, somehow became essentially unchangeable.

As is typical of the evolution genre, all of this is expressed in teleological terms. Here is a paragraph from the paper that is loaded with evolution’s Aristotelian tendencies:

Lowe et al. proposed that, within vertebrates, there have been three distinct periods of CNE [conserved non-coding element] recruitment around specific groups of genes. They suggest that this pattern is the result of regulatory innovations, which led to important phenotypic changes during vertebrate evolution. Prior to the divergence of mammals from reptiles and birds, it appears that CNEs were preferentially recruited near TFs and their developmental targets. This was followed by a gradual decline in recruitment near these genes, accompanied by [a recruitment] increase near proteins involved in extracellular signalling, and then [a recruitment] increase in placental mammals near genes responsible for post-translational modification and intracellular signalling. An analysis of CNE gain in the primate and rodent lineage has found that CNEs are either recruited near genes which have not previously been associated with CNEs, or are added near genes which are already flanked by CNEs. The interpretation was that the first set of genes is enriched in functions pertaining to nervous system development, whereas the latter contains genes involved in transcriptional regulation and anatomical development.

This example of teleological language also illustrates how the commitment to a theory can lead to a loss of parsimony. That is, in order to accommodate new and contradictory findings, additional explanations must be added to the theory. It becomes more complicated and less parsimonious. Here is how the paper summarizes these findings of extreme sequence conservation:

… despite 10 years of research, there has been virtually no progress towards answering the question of the origin of these patterns of extreme conservation. A number of hypotheses have been proposed, but most rely on modes of DNA : protein interactions that have never been observed and seem dubious at best. As a consequence, not only do we still lack a plausible mechanism for the conservation of CNEs—we lack even plausible speculations.

Reasonable speculation and even solutions to extreme sequence conservation may come in the future. But today’s science once again highlights the unique status of evolution.

Regulating the Regulators: A Single Arginine Insertion in the Glucocorticoid Receptor Changes Protein Expression

Damage Control Underway

Not only is evolution a fact beyond all reasonable doubt, it also is essential to ones understanding of biology. Indeed, without evolution, science itself would be impossible. These are the pronouncements of evolutionists who even go so far as to define life as the ability to evolve. Given these truths one would think that evolutionary theory would be rather important for research in the life sciences. Is not the evolutionary framework a necessary starting point? Surprisingly scientific progress consistently is made without evolution leading the way or even pointing in the right direction. Often evolutionists are surprised by the science and new evolutionary explanations are tacked on after the fact rather than providing the initial insight. Other times evolution simply is not even mentioned as it simply makes no sense on the science.

Consider, for example, transcription factors—proteins that influence and control the transcription of genes, which leads to the synthesis of new proteins. Evolution cannot explain how these genetic regulators evolved, and even if they did somehow evolve they don’t fit the expected evolutionary pattern.

But that’s only the beginning. Transcription factors operate according to instructions and codes that also don’t fit the evolutionary pattern, and their mechanisms are incredibly complex, including secondary regulation where a transcription factor influences a different transcription factor. You can read more about these marvels here, here and here.

Now new research on the glucocorticoid receptor—a transcription factor that, for example, helps to activate sugar production in the liver—presents yet more contradictions to evolutionary theory.

The glucocorticoid receptor has several components, one of which is a lever arm. After the glucocorticoid receptor gene is transcribed (a process that is influenced by yet other transcription factors), the messenger RNA transcript can be edited to produce different versions of the glucocorticoid receptor protein. In one such version a single arginine amino acid is inserted into the lever arm region. This single modification influences both how the different glucocorticoid receptor components communicate, and what types of DNA sequences the glucocorticoid receptor is likely to bind to. The result of all this is a change in the genes which are regulated and the magnitude of their regulation.

The editing machinery that inserts the single arginine amino acid is incredibly complicated. Under evolution we would have to believe that random mutations just happened to construct the fantastic editing machinery, a feat for which there is no explanation.

But evolution would have to repeat these heroics a large number of times to search through the astronomical number of different edits that are possible. How many amino acids should be edited? Should they be deleted or added? Which amino acids should be used? On which gene transcripts should the editing be performed? And where in the transcript should the edit be made?

And how did the evolutionists respond to these findings? In spite of the fact that this arginine insertion edit occurs in widespread species, they wonder if the whole operation isn’t just a mistake. A simple consequence of erroneous editing that is tolerated.

This is always the first guess of evolutionary theory. For if all of biology spontaneously arose via chance events, then we should expect to find a collection of broken or barely functional designs. But in the inexorable march of science, such assumptions are inevitably found to be false. Functional reasons are discovered, ascribed to evolution’s natural selection, and then it is on to the next finding which is assumed to be yet another erroneous design because, after all, evolution is a fact.

Evolutionists Are Celebrating a New Chimp-Human Study That Actually Just Presents More Problems

They Just Aren’t That Smart

Remember how nearly-identical chimpanzee-human genes were celebrated as yet another proof of evolution? There was only one problem: it didn’t make sense because the genes were too similar. The minor differences were probably not enough to produce species as different as the chimp and human and, as I explained in my book Darwin’s Proof, there must be more significant differences to be found between the two primates. And indeed such differences were discovered. One was that even those highly similar genes were often transcribed at very different levels in the two species. This, evolutionists reasoned, must have been a driver in the primate evolution that led to such different species. What evolutionists did not realize was that, once again, they had violated Occam’s Razor by adding yet more serendipity to their theory. With evolution we were to believe that essentially all the genes needed to make humans evolved first and then later the quantities were adjusted to evolve homo sapiens. Imagine an inventor who just luckily builds all the parts of a Boeing 747 but not in the right quantities. He has only one wing, three rudders, a dozen jet engines, and so forth. Then he realizes how well the parts work together if he merely adjusts the quantities a bit. Now a new study shows another problem with evolution’s just-so story of human evolution.

The new study shows that the differing transcription levels in chimps and humans do not correlate very well to differing protein expression levels. In other words, a gene may be copied more or less frequently, but that does not necessarily mean the resulting protein will be produced at higher or lower amounts.

Various patterns were observed and the evolutionists now reason that protein expression levels evolve under greater evolutionary constraint than gene transcription, via some unknown or unidentified mechanism.

Notice that evolutionary theory is completely superfluous to the story. The study made a scientific discovery, but it was then wrapped in an evolutionary narrative that does not help us to understand the new finding and adds nothing to the science. Furthermore, the evolution narrative, in spite of its uncertainty and vagueness, is presented as a fact. Evolutionists just aren’t that smart.

The Damsel Fish and its Amazing Survival Strategies

Multiplying Entities

When young damsel fish (Pomacentrus amboinensis) are in danger their eyes shrink while they grow false eyespots on their tail to fool their predators. They also undergo other morphological and behavior changes to escape attack. Research out of Australia not only elucidated these tactics but demonstrated that they work, increasing the survival rate of the young fish by an amazing five-fold. And while the researchers had to admit that all of this was “an amazing feat of cunning for a tiny fish,” they nonetheless ignored Occam’s advice and multiplied entities when they added nothing to the science by ascribing it all to random chance (No natural selection does not induce the good mutations to occur, it merely kills off the bad ones—every mutation leading up to the damsel and its “amazing” capabilities must be random with respect to need. Selection doesn’t magically make fantastic designs appear.):

It all goes to show that even a very young, tiny fish a few millimetres long have evolved quite a range of clever strategies for survival which they can deploy when a threatening situation demands.

It all goes to show? In fact, to be a bit more precise, none of it shows the damsel evolved. That’s right, even though the evolutionists claim that “it all goes to show” that the clever strategies evolved, from an empirical science perspective, none of the evidence shows any such thing.

All versus none—that’s quite a gap between evolutionary thought and science. As usual evolution is the contra indicator. It abuses science, turning it upside down to support its preconceived, mandated result.

Why Penguins Can’t Fly

Another Violation of Ockam’s Razor

One of the problems Aristotelianism faced in the sixteenth century was that it had become gratuitous. A hot fire dried out a damp cloth because, Aristotelians explained, fire has the quality of dryness and heat. But these were nothing more than descriptive labels. The qualities did not explain how the fire dried the cloth. As Descartes later complained:

If you find it strange that … I do not use the qualities called “heat,” “cold,” “moistness,” and “dryness,” as do the philosophers, I shall say to you that these qualities appear to me to be themselves in need of explanation.

Descartes helped to defeat Aristotelianism but as it faded a similar form of explanation emerged to replace it. Like Aristotelianism this new, but not really new, program tended to rely on goal-seeking, teleological explanations. And like Aristotelianism the new program failed to fulfill the Cartesian criterion of explaining how. And like Aristotelianism the new program’s followers were certain it was true. That new program provided a foundation for Charles Darwin and is now called evolution.

Consider for example a recent paper explaining why penguins cannot fly. The answer, it seems, is that through evolution penguins lost the ability to fly as they gained their fantastic swimming skills. The physics of swimming and flying do not go well together and if a species is a great swimmer then it won’t be able to fly very well, if at all. Diving into the water must have been more important to the penguin so it evolved swimming skills at the cost of losing its flying abilities. It was an evolutionary tradeoff.

But the evolution part, like the Aristotelian qualities, is gratuitous. In yet another violation of Ockam’s Razor the evolutionists continue to multiply entities. You see the actual science that was done had nothing to do with evolution. Instead what the science suggested is that good swimming and good flying skills likely do not easily fit into one package.

What the scientific analysis did not find was any explanation for how the penguins could have undergone such an evolutionary transition, let alone how penguins could have evolved in the first place.

The explanation is, itself, in need of explanation.

In fact, the scientific evidence does not indicate that penguins, and all the rest of biology for that matter, arose spontaneously. Yet evolutionists claim this is a fact.

The king (Aristotelianism) is dead, long live the king (Darwinism).

Gene Expression Evolution: Your Daily Teleology …

Here is a new paper that claims to show the rate of gene expression evolution in a range of different mammalian species. Of course the paper shows no such thing. What it does show are gene expression rates in extant species. And what they found is that those rates are all over the map. The rates are often similar, but in other cases the rates not only vary between species, they also vary between organs and even chromosomes. As usual, the evolutionists describe the findings using teleological language to cover over what evolution really says:

We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation.

Of course there is no such thing as “selective pressure.” This phrase is commonly used to envision an active process that responds to environmental challenges. If natural selection shapes and designs the species according to need, then it sounds more plausible. In reality, all natural selection does is kill off the bad designs.

Although gene expression evolution in mammals was strongly shaped by purifying selection, …

Translation: The evolutionists found that many cases similar genes have similar expression rates.

we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals.

In other words, the evolutionists also found some similar genes that have significantly different expression rates. So the evolutionists must infer a new kind of evolution. Instead of mutations grinding away which, on rare occasion, provide a slightly better design (in terms of reproduction of course), the new kind of evolution states that the genes and their regulation mechanisms are generally already in place. What changes is their expression rates. So evolution created all these genes and regulation mechanisms, no knowing that it had just created the building blocks for all massive biological complexity. All that was needed was some expression rate changes.

Aside from being unlikely, evolution calls for massive serendipity. As usual, it is presented in teleological terms.

Brian Cusack’s Latest: Anti Parsimonious, Teleological, Petitio Principii, Cum Hoc Ergo Propter Hoc and Misrepresentations—Other Than That It’s Perfect

Or should we say, it is perfect, for creatively finding new ways to cram as many fallacies as possible into a single paper is precisely what “scientific” evolutionism seems to be all about. Cusack’s latest peer-reviewed contribution to the evolution literature, Preventing Dangerous Nonsense: Selection for Robustness to Transcriptional Error in Human Genes, is perfectly typical. But alas, due to the strict page limits of Darwin’s God, we are only able to provide a mere brief overview.

Background

When a gene is used to synthesize a protein, error checking and prevention is performed all along the way. An important and dangerous error is the so-called nonsense error in which the code for an amino acid is erroneously replaced with a stop signal. This causes the protein synthesis process to be halted in mid stream, leaving a half-baked and useless segment of protein. Cell’s have various processes to check for and correct such nonsense errors, but another way around the problem is to avoid the genetic coding that is particularly susceptible to nonsense errors.

Anti parsimonious

The main contribution of Cusack’s paper is its elucidation of how these correction and prevention mechanisms often complement each other nicely. In particular, the error correction mechanisms have their limitations. One of the correction mechanisms usually doesn’t work for genes that are written out in one, single continuous region. And for genes that are divided into several separate regions, that mechanism often doesn’t work for the final region.

It is in these particular regions—where the error correction is more limited—that the prevention is stronger. In these regions, the particular genetic coding that is susceptible to nonsense errors is diminished. It would be like having a spell-checker that cannot check a certain page, but that page doesn’t have any long words to begin with.

This and other examples need nothing more than common sense to understand. Looking at the design of the error correction and prevention mechanisms, it makes perfect sense that where the error correction is less effective, there would be more error prevention. Nonetheless, the evolutionists break every rule of parsimony to impose their evolutionary framework. They multiply entities and construct superfluous causes. From Occam to Einstein we know not to do this, but evolutionists must have their theory. Here are two examples from the paper:

Given the high rate of transcriptional errors in eukaryotes, we hypothesized that natural selection has promoted a dual strategy of “prevention and cure” to alleviate the problem of nonsense transcriptional errors. A prediction of this hypothesis is that [the error correction’s] inefficiency should leave a signature of “transcriptional robustness” in human gene sequences that reduces the frequency of nonsense transcriptional errors.

[…]

Interestingly, one group of genes falls entirely outside of the range of [the error correction’s] surveillance. Replication-dependent histones contain neither introns in their coding sequences nor polyA-tail in their mRNAs. Therefore, histone genes represent a blind-spot for both mammalian [the error correction] pathways. According to our hypothesis histone genes should represent the most transcriptionally robust genes in the mammalian genome since PTC-containing transcripts of their genes will not be recognized and degraded before translation.

Evolution adds nothing to the science here. These are yet more examples of how evolution is a gratuitous explanation, adding nothing but “multiplied entities” as Occam put it. We may as well say, with the Aristotelians, that fire is hot because it has the quality of heat.

Teleological

Evolution adds little to the science beyond gratuitous explanation, and furthermore that explanation is awkward. The theory states that the entire biological world just happened to arise all by itself.

Not surprisingly evolutionists never describe it this way. Nor do they use equally accurate but more detailed explanations, such as that blind mutations just happened to create complex, interdependent designs while natural selection killed off the bad designs. Such accurate explanations of the theory are not used because they make obvious the absurdity of the whole project.

Instead evolutionists craft clever explanations that cast evolution and its natural selection in the active role of a designer. The theory sounds so much more plausible when natural selection responds to a need by creating a new design. And so there is an underlying, latent Lamarckianism running through the evolution genre. Out of one side of their mouth they rail against teleology while from the other they appeal to it over and over. Here are typical examples from the paper:

we hypothesized that natural selection has promoted a dual strategy of “prevention and cure” to alleviate the problem of nonsense transcriptional errors.

[…]

Nonsense errors are potentially highly toxic for the cell, so natural selection has evolved a strategy called Nonsense Mediated Decay (NMD) to “cure” such errors.

[…]

Moreover, these “prevention and cure” strategies are used interchangeably …

Natural selection has promoted a dual strategy to alleviate a problem? Strategies are used interchangeably? Of course evolutionists do not mean any of this to be true. Their teleology is rhetorical. They need it to avoid the literal.

Petitio principii

The evolutionists force-fit the evidence into their theory, and the fit isn’t very good. Cusack’s flawed thesis is that evolution predicts how the error correction and prevention methods complement each other. But as usual the project depends on the pre existence of biology’s wonders. In this case, the evolutionists believe that evolution just happened to create the genetic code, which conveniently just happened to have some stop signals.

Evolution also just happened to create genetic information, including stop signs at the appropriate places, and the incredible molecular machines to read, copy and translate that genetic information, and to stop at the stop signs.

But sometimes errors occurred which inserted stop signs somewhere in the middle of a copy of a gene. Fortunately, evolution just happened to create incredible molecular machinery and mechanisms to check for and correct for such errors. The likelihood of all (or any) of this happening is of course beyond ridiculous. The theory isn’t even wrong.

The only way to avoid evolution’s massive contradictions is simply to assume it is true. Having swallowed such lunacy the evolutionists are now in a position to declare that the new evidence is yet another fulfilled prediction of, yes, evolution. Evolution is true, therefore evolution is true.

Cum hoc ergo propter hoc

A common evolutionary fallacy is to confuse correlation with causation. In this case Cusack and the evolutionists find a good correlation between the correction and prevention mechanisms. Simply put, where the correction is weaker, the prevention is stronger. And so they assume the former is the cause of the latter via the evolutionary process:

We observe that single-exon genes have evolved to become robust to mistranscription, because they show a significant tendency to avoid fragile codons relative to robust codons when compared to multi-exon genes.

[…]

Depletion of fragile codons is due primarily to inactivity of EJC–dependent NMD but also to reduced efficiency of PABP–dependent NMD.

[…]

We show that variable NMD efficiency also leaves its signature in the coding sequences of human genes and in the amino-acid content of the proteins they encode.

When will evolutionists learn that correlation does not imply causation. The answer of course is that they will learn this only when they learn to stop corrupting science with their religious dogma. That may sound harsh, but that is precisely what evolutionists are doing. Their metaphysics mandates evolution to be true. Therefore such correlations must be assumed to be the result of evolutionary causation.

Misrepresentations

No evolutionary treatise would be complete without misrepresentations of the science. If there is any common thread to scientific evolutionism it is the very bizarre interpretations of the scientific evidence which, to put it kindly, amount to misrepresentations. Such misrepresentations run all though the genre, from the popular works on down to the technical papers. Consider these misrepresentations from Cusack’s paper:

In contrast, gene expression errors are not inherited and have tended to be disregarded in evolutionary studies. Here we show how human genes have evolved a mechanism to reduce the occurrence of a specific type of gene expression error—transcriptional errors that create premature STOP codons (so-called “nonsense errors”).

But of course the paper showed no such thing. It did not “show how human genes have evolved a mechanism …” That is an incredibly unlikely, religiously-driven hypothesis that makes little scientific sense. The paper continues:

Nonsense errors are potentially highly toxic for the cell, so natural selection has evolved a strategy called Nonsense Mediated Decay (NMD) to “cure” such errors. However this cure is inefficient. Here we describe how a preventative strategy of “transcriptional robustness” has evolved to decrease the frequency of nonsense errors.

These are yet more blatant misrepresentations of the science. The paper does not “describe how a preventative strategy of ‘transcriptional robustness’ has evolved to decrease the frequency of nonsense errors.” The paper not only did not describe how such a strategy evolved, it did not even show that it evolved.

Religion drives science, and it matters.

Did the Seabird Evolve Head Feathers as Sensory Device?

New research shows that without their head feathers seabirds such as Aethia cristatella can’t find their way through tight spaces as well:

Crested and whiskered auklets nest in hollows on rocky islands in the remote northern Pacific Ocean. To see if their elaborate headdresses helped the birds make their way through the rocks to their nests at night, Jones and Seneviratne went to the Aleutian Islands, captured wild birds and put them in a darkened maze – but first they taped down some birds' decorative feathers.

Infrared camera recordings showed that whiskered auklets (Aethia pygmaea) bumped their heads nearly three times more often if their long head feathers were taped down. Crested auklets (A. cristatella), suffered similarly with their crests taped down, but adding an artificial crest to the naturally unadorned least auklet (A. pusilla) – which also nests on the islands but in more open areas – didn't help these birds avoid bumps. Moreover, Sereviratne says, "birds with longer crests had greater difficulty in navigating inside the maze" when their crests were taped down.

The evolutionary origin of the birds' elaborate head feathers supports the idea that their first job was sensing, says Seneviratne. He adds that the auklets' crests evolved from filoplumes, long hair- or thread-like feathers that lack normal feather structures and are attached to pressure-sensitive cells so they can detect touch. In many birds these feathers are hidden by larger contour or wing feathers, but in the auklets they stick out proudly where they can detect obstacles.

The auklet’s head feathers clearly are not just for looks. But evolutionary theory was not needed to make this discovery, nor does it help in explaining the feathers, or the cellular pressure-sensing mechanisms. In fact, beyond empty speculation evolution has no explanation for how such mechanisms could have arisen on their own. It is a typical example of how evolution is a gratuitous explanation, adding nothing but a “multiplied entity” as Occam put it. We may as well say, with the Aristotelians, that fire is hot because it has the quality of heat. Not only has evolutionary theory badly failed, it is not particularly helpful in doing science. It simply becomes more and more complex as we learn about the world.