Wintery Knight

…integrating Christian faith and knowledge in the public square

Dr. Stephen C. Meyer lectures on intelligent design and the origin of life

A MUST-SEE lecture based on Dr. Stephen C. Meyer’s book “Signature in the Cell“.

You can get an MP3 of the lecture here. (30 MB)

I highly recommend watching the lecture, and looking at the slides. The quality of the video and the content is first class. There is some Q&A (9 minutes) at the end of the lecture.

Topics:

  • intelligent design is concerned with measuring the information-creating capabilities of natural forces like mutation and selection
  • Darwinists think that random mutations and natural selection can explain the origin and diversification of living systems
  • Darwinian mechanisms are capable of explaining small-scale adaptive changes within types of organisms
  • but there is skepticism, even among naturalists, that Darwinian mechanisms can explain the origin of animal designs
  • even if you concede that Darwinism can account for all of the basic animal body plans, there is still the problem of life’s origin
  • can Darwinian mechanisms explain the origin of the first life? Is there a good naturalistic hypothesis to explain it?
  • there are at least two places in the history of life where new information is needed: origin of life, and Cambrian explosion
  • overview of the structure of DNA and protein synthesis (he has helpful pictures and he uses the snap lock blocks, too)
  • the DNA molecule is composed of a sequence of proteins, and the sequence is carefully selected to have biological function
  • meaningful sequences of things like computer code, English sentences, etc. require an adequate cause
  • it is very hard to arrive at a meaningful sequence of a non-trivial length by randomly picking symbols/letters
  • although any random sequence of letters is improbable, the vast majority of sequences are gibberish/non-compiling code
  • similarly, most random sequences of amino acids are lab-proven (Doug Axe’s work) to be non-functional gibberish
  • the research showing this was conducted at Cambridge University and published in the Journal of Molecular Biology
  • so, random mutation cannot explain the origin of the first living cell
  • however, even natural selection coupled with random mutation cannot explain the first living cell
  • there must already be replication in order for mutation and selection to work, so they can’t explain the first replicator
  • but the origin of life is the origin of the first replicator – there is no replication prior to the first replicator
  • the information in the first replicator cannot be explained by law, such as by chemical bonding affinities
  • the amino acids are attached like magnetic letters on a refrigerator
  • the magnetic force sticks the letters ON the fridge, but they don’t determine the specific sequence of the letters
  • if laws did determine the sequence of letters, then the sequences would be repetitive
  • the three materialist explanations – chance alone, chance and law, law alone – are not adequate to explain the effect
  • the best explanation is that an intelligent cause is responsible for the biological explanation in the first replicator
  • we know that intelligent causes can produce functional sequences of information, e.g. – English, Java code
  • the structure and design of DNA matches up nicely with the design patterns used by software engineers (like WK!)

There are some very good tips in this lecture so that you will be able to explain intelligent design to others in simple ways, using everyday household items and children’s toys to symbolize the amino acids, proteins, sugar phosphate backbones, etc.

Proteins are constructed from a sequence of amino acids:

A sequence of amino acids forming a protein

A sequence of amino acids forming a protein

Proteins sticking onto the double helix structure of DNA:

Some proteins sticking onto the sugar phosphate backbone

Some proteins sticking onto the sugar phosphate backbone

I highly, highly recommend this lecture. You will be delighted and you will learn something.

Here is an article that gives a general overview of how intelligent design challenges. If you want to read something more detailed about the material that he is covering in the lecture above related to the origin of life, there is a pretty good article here.

UPDATE: There is a good breakdown of some of the slides with helpful flow charts here on Uncommon Descent.

Positive arguments for Christian theism

Filed under: Videos, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Convergence detected in the genetic structure of bats and dolphins

We have to start this post with the definition of convergence in biology.

In evolutionary biology, convergent evolution is the process whereby organisms not closely related (not monophyletic), independently evolve similar traits as a result of having to adapt to similar environments or ecological niches.

It is the opposite of divergent evolution, where related species evolve different traits.

On a molecular level, this can happen due to random mutation unrelated to adaptive changes; see long branch attraction. In cultural evolution, convergent evolution is the development of similar cultural adaptations to similar environmental conditions by different peoples with different ancestral cultures. An example of convergent evolution is the similar nature of the flight/wings of insects, birds, pterosaurs, and bats.

All four serve the same function and are similar in structure, but each evolved independently.

Jonathan Wells explains the problem that convergence poses for naturalistic evolution:

Human designers reuse designs that work well. Life forms also reuse certain structures (the camera eye, for example, appears in humans and octopuses). How well does this evidence support Darwinian evolution? Does it support intelligent design more strongly?

Evolutionary biologists attribute similar biological structures to either common descent or convergence. Structures are said to result from convergence if they evolved independently from distinct lines of organisms. Darwinian explanations of convergence strain credulity because they must account for how trial-and-error tinkering (natural selection acting on random variations) could produce strikingly similar structures in widely different organisms and environments. It’s one thing for evolution to explain similarity by common descent—the same structure is then just carried along in different lineages. It’s another to explain it as the result of blind tinkering that happened to hit on the same structure multiple times. Design proponents attribute such similar structures to common design (just as an engineer may use the same parts in different machines). If human designers frequently reuse successful designs, the designer of nature can surely do the same.

I’m a software engineer, and we re-use components all the time for different programs that have no “common ancestor”. E.g. – I can develop my String function library and use it in my web application and my Eclipse IDE plug-in, and those two Java programs have nothing in common. So you find the same bits in two different programs because I am the developer of both programs. But the two programs don’t extend from a common program that was used for some other purpose – they have no “common ancestor” program.

Now with that in mind, take a look at this recent article from Science Daily, which Mysterious Micah sent me.

Excerpt:

The evolution of similar traits in different species, a process known as convergent evolution, is widespread not only at the physical level, but also at the genetic level, according to new research led by scientists at Queen Mary University of London and published in Nature this week.

The scientists investigated the genomic basis for echolocation, one of the most well-known examples of convergent evolution to examine the frequency of the process at a genomic level.

Echolocation is a complex physical trait that involves the production, reception and auditory processing of ultrasonic pulses for detecting unseen obstacles or tracking down prey, and has evolved separately in different groups of bats and cetaceans (including dolphins).

The scientists carried out one of the largest genome-wide surveys of its type to discover the extent to which convergent evolution of a physical feature involves the same genes.

They compared genomic sequences of 22 mammals, including the genomes of bats and dolphins, which independently evolved echolocation, and found genetic signatures consistent with convergence in nearly 200 different genomic regions concentrated in several ‘hearing genes’.

[...]Consistent with an involvement in echolocation, signs of convergence among bats and the bottlenose dolphin were seen in many genes previously implicated in hearing or deafness.

“We had expected to find identical changes in maybe a dozen or so genes but to see nearly 200 is incredible,” explains Dr Joe Parker, from Queen Mary’s School of Biological and Chemical Sciences and first author on the paper.

“We know natural selection is a potent driver of gene sequence evolution, but identifying so many examples where it produces nearly identical results in the genetic sequences of totally unrelated animals is astonishing.”

Nature is the most prestigious peer-reviewed science journal. This is solid material.

There is an earlier article from 2010 in New Scientist that talked about one of the previous genes that matched for hearing capability.

Excerpt:

Bats and dolphins trod an identical genetic path to evolve a vital component of the complex sonar systems they use to pursue and catch prey.

The finding is unusual, because although many creatures have independently evolved characteristics such as eyes, tusks or wings, they usually took diverse genetic routes to get there.

Analysis of a specific gene has now demonstrated that although bats live in air and dolphins in water, where sound travels five times faster, they independently evolved a near-identical gene that allows them to accept high-frequency sound in the ear – vital for sonar.

The gene makes prestin, a protein in hair cells of the cochlea, which is the organ in the inner ear where sonar signals are accepted and amplified. Prestin changes shape when exposed to high-frequency sound, and this in turn deforms the fine hair cells, setting off an electrical impulse to the brain. So the protein has the important jobs of detecting and selecting high-frequency sounds for amplification.

When researchers examined the molecular structure of the prestin gene from a range of animals, they found that the variants in echolocating bats and dolphins were virtually indistinguishable.

Indistinguishable genes in animals that don’t share a common ancestor? Maybe a better explanation for the evidence we have is – common designer.

Filed under: News, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

What is intelligent design? Dr. Stephen C. Meyer explains the theory

A MUST-SEE lecture based on Dr. Stephen C. Meyer’s book “Signature in the Cell“.

You can get an MP3 of the lecture here. (30 MB)

I highly recommend watching the lecture, and looking at the slides. The quality of the video and the content is first class. There is some Q&A (9 minutes) at the end of the lecture.

Topics:

  • intelligent design is concerned with measuring the information-creating capabilities of natural forces like mutation and selection
  • Darwinists think that random mutations and natural selection can explain the origin and diversification of living systems
  • Darwinian mechanisms are capable of explaining small-scale adaptive changes within types of organisms
  • but there is skepticism, even among naturalists, that Darwinian mechanisms can explain the origin of animal designs
  • even if you concede that Darwinism can account for all of the basic animal body plans, there is still the problem of life’s origin
  • can Darwinian mechanisms explain the origin of the first life? Is there a good naturalistic hypothesis to explain it?
  • there are at least two places in the history of life where new information is needed: origin of life, and Cambrian explosion
  • overview of the structure of DNA and protein synthesis (he has helpful pictures and he uses the snap lock blocks, too)
  • the DNA molecule is composed of a sequence of proteins, and the sequence is carefully selected to have biological function
  • meaningful sequences of things like computer code, English sentences, etc. require an adequate cause
  • it is very hard to arrive at a meaningful sequence of a non-trivial length by randomly picking symbols/letters
  • although any random sequence of letters is improbable, the vast majority of sequences are gibberish/non-compiling code
  • similarly, most random sequences of amino acids are lab-proven (Doug Axe’s work) to be non-functional gibberish
  • the research showing this was conducted at Cambridge University and published in the Journal of Molecular Biology
  • so, random mutation cannot explain the origin of the first living cell
  • however, even natural selection coupled with random mutation cannot explain the first living cell
  • there must already be replication in order for mutation and selection to work, so they can’t explain the first replicator
  • but the origin of life is the origin of the first replicator – there is no replication prior to the first replicator
  • the information in the first replicator cannot be explained by law, such as by chemical bonding affinities
  • the amino acids are attached like magnetic letters on a refrigerator
  • the magnetic force sticks the letters ON the fridge, but they don’t determine the specific sequence of the letters
  • if laws did determine the sequence of letters, then the sequences would be repetitive
  • the three materialist explanations – chance alone, chance and law, law alone – are not adequate to explain the effect
  • the best explanation is that an intelligent cause is responsible for the biological explanation in the first replicator
  • we know that intelligent causes can produce functional sequences of information, e.g. – English, Java code
  • the structure and design of DNA matches up nicely with the design patterns used by software engineers (like WK!)

There are some very good tips in this lecture so that you will be able to explain intelligent design to others in simple ways, using everyday household items and children’s toys to symbolize the amino acids, proteins, sugar phosphate backbones, etc.

Proteins are constructed from a sequence of amino acids:

A sequence of amino acids forming a protein

A sequence of amino acids forming a protein

Proteins sticking onto the double helix structure of DNA:

Some proteins sticking onto the sugar phosphate backbone

Some proteins sticking onto the sugar phosphate backbone

I highly, highly recommend this lecture. You will be delighted and you will learn something.

Here is an article that gives a general overview of how intelligent design challenges. If you want to read something more detailed about the material that he is covering in the lecture above related to the origin of life, there is a pretty good article here.

Related posts

Filed under: Videos, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

What is intelligent design? Dr. Stephen C. Meyer explains the theory

A MUST-SEE lecture based on Dr. Stephen C. Meyer’s book “Signature in the Cell“. (H/T Chris S.)

You can get an MP3 of the lecture here. (30 MB)

I highly recommend watching the lecture, and looking at the slides. The quality of the video and the content is first class. There is some Q&A (9 minutes) at the end of the lecture.

Topics:

  • intelligent design is concerned with measuring the information-creating capabilities of natural forces like mutation and selection
  • Darwinists think that random mutations and natural selection can explain the origin and diversification of living systems
  • Darwinian mechanisms are capable of explaining small-scale adaptive changes within types of organisms
  • but there is skepticism, even among naturalists, that Darwinian mechanisms can explain the origin of animal designs
  • even if you concede that Darwinism can account for all of the basic animal body plans, there is still the problem of life’s origin
  • can Darwinian mechanisms explain the origin of the first life? Is there a good naturalistic hypothesis to explain it?
  • there are at least two places in the history of life where new information is needed: origin of life, and Cambrian explosion
  • overview of the structure of DNA and protein synthesis (he has helpful pictures and he uses the snap lock blocks, too)
  • the DNA molecule is composed of a sequence of proteins, and the sequence is carefully selected to have biological function
  • meaningful sequences of things like computer code, English sentences, etc. require an adequate cause
  • it is very hard to arrive at a meaningful sequence of a non-trivial length by randomly picking symbols/letters
  • although any random sequence of letters is improbable, the vast majority of sequences are gibberish/non-compiling code
  • similarly, most random sequences of amino acids are lab-proven (Doug Axe’s work) to be non-functional gibberish
  • the research showing this was conducted at Cambridge University and published in the Journal of Molecular Biology
  • so, random mutation cannot explain the origin of the first living cell
  • however, even natural selection coupled with random mutation cannot explain the first living cell
  • there must already be replication in order for mutation and selection to work, so they can’t explain the first replicator
  • but the origin of life is the origin of the first replicator – there is no replication prior to the first replicator
  • the information in the first replicator cannot be explained by law, such as by chemical bonding affinities
  • the amino acids are attached like magnetic letters on a refrigerator
  • the magnetic force sticks the letters ON the fridge, but they don’t determine the specific sequence of the letters
  • if laws did determine the sequence of letters, then the sequences would be repetitive
  • the three materialist explanations – chance alone, chance and law, law alone – are not adequate to explain the effect
  • the best explanation is that an intelligent cause is responsible for the biological explanation in the first replicator
  • we know that intelligent causes can produce functional sequences of information, e.g. – English, Java code
  • the structure and design of DNA matches up nicely with the design patterns used by software engineers (like WK!)

There are some very good tips in this lecture so that you will be able to explain intelligent design to others in simple ways, using everyday household items and children’s toys to symbolize the amino acids, proteins, sugar phosphate backbones, etc.

Proteins are constructed from a sequence of amino acids:

A sequence of amino acids forming a protein

A sequence of amino acids forming a protein

Proteins sticking onto the double helix structure of DNA:

Some proteins sticking onto the sugar phosphate backbone

Some proteins sticking onto the sugar phosphate backbone

I highly, highly recommend this lecture. You will be delighted and you will learn something.

Here is an article that gives a general overview of how intelligent design challenges. If you want to read something more detailed about the material that he is covering in the lecture above related to the origin of life, there is a pretty good article here.

Related posts

Filed under: Videos, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Can Darwinian evolution create new functional biological information?

Here’s a great article from Evolution News that explains the trouble that Darwinian evolution has in building up to functional new biological information by using a process of random mutation and natural selection.

Casey Luskin takes a look at a peer-reviewed paper that claims that Darwinian evolution can do the job of creating new information, then he explains what’s wrong with the paper.

Excerpt:

In Wilf and Ewens’s evolutionary scheme there is a smooth fitness function. Under this view, there is no epistasis, where one mutation can effectively interact with another to affect (whether positively or negatively) fitness. As a result, any mutations that move the search toward its “target” are assumed to provide an immediate and irrevocable advantage, and are thus highly likely to become fixed. Ewert et al. compare the model to playing Wheel of Fortune:

The evolutionary model that Wilf and Ewens have chosen is similar to the problem of guessing letters in a word or phrase, as on the television game show Wheel of Fortune. They specify a phrase 20,000 letters long, with each letter in the phrase corresponding to a gene locus that can be transformed from its initial “primitive” state to a more advanced state. Finding the correct letter for a particular position in the target phrase roughly corresponds to finding a beneficial mutation in the corresponding gene. During each round of mutation all positions in the phrase are subject to mutation, and the results are selected based on whether the individual positions match the final target phrase. Those that match are preserved for the next round. … After each round, all “advanced” alleles in the population are treated as fixed, and therefore preserved in the next round. Evolution to the fully “advanced” state is complete when all 20,000 positions match the target phrase.

The problem with this approach is that a string of biological information that has only some letters that are part of a useful sequence has no present function, and therefore cannot survive and reproduce.

Look:

Thus, Wilf and Ewens ignore the problem of non-functional intermediates. They assume that all intermediate stages will be functional, or lead to some functional advantage. But is this how all fitness functions look? Not necessarily. It’s well known that in many instances, no benefit is derived until multiple mutations are present all at once. In such a case, there’s no evolutionary advantage until multiple mutations are present. The “correct” mutations might occur in parallel, but the odds of this happening are extremely low. Ewert et al. illustrate this problem in the model by using the example of the difficulty of one phrase evolving into another:

Suppose it would be beneficial for the phrase

“all_the_world_is_a_stage___”

to evolve into the phrase

“methinks_it_is_like_a_weasel.”

What phrase do we get if we simply alternate letters from the two phrases?

“mlt_ihk__otli__siaesaaw_a_e_.”

Under the assumptions in the Wilf and Ewens model, the “fitness” of this nonsense phrase ought to be exactly half-way between the fitnesses of “all the world is a stage” and “methinks it is like a weasel.” Such a result only makes sense if we are measuring the fitness of the current phrase by its proximity to the target phrase.

But the gibberish of the intermediate phrase doesn’t cause any problem under Wilf and Ewens’s model. Not unlikeRichard Dawkins, they assume that intermediate stages will always yield some functional advantage. And as more and more characters in the phrase match the target, it becomes more and more fit. This yields a nice, smooth fitness function — rich in active information — not truly a blind search.

Not only is there that first problem, but here’s a second:

Wilf and Ewens endowed their mathematical model of evolution with foresight. It is directed toward a target — an advantage that natural selection conspicuously lacks. And what, in our experience, is the only known cause that is goal-directed and has foresight? It’s intelligence. This means that once again, the Evolutionary Informatics Lab has shown that simulations of evolution seem to work only because they’ve been intelligently designed.

This is worth the read. If Darwinian mechanisms really could generate code, then there would be no software engineers. The truth is, the mechanisms don’t work to create new information. For that, you need an intelligent designer.

Filed under: Polemics, , , , , , , , , , , , , , , , , , , , , ,

Wintery Tweets

Click to see recent visitors

  Visitors Online Now

Page views since 1/30/09

  • 3,944,214 hits

Enter your email address to follow this blog and receive notifications of new posts by email.

Join 1,729 other followers

Archives

Follow

Get every new post delivered to your Inbox.

Join 1,729 other followers

%d bloggers like this: