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PART III: ANNOTATED BIBLIOGRAPHY OF PEER-REVIEWED PUBLICATIONS
Category 1: Peer-Reviewed Scientific Publications Supportive of Intelligent Design
• James Johansen, “Bacterial chemotaxis control process analysis with SysML,” Systems Engineering, 2024: 1-23 (2024).
[https://incose.onlinelibrary.wiley.com/doi/10.1002/sys.21752 ]
James Johansen is a design-friendly professor of engineering at Biola University who specializes in applying engineering principles and tools to biological research.
His article demonstrates how applying the systems engineering modeling tool SysML to bacterial chemotaxis (i.e., navigation) yields valuable insights into its global design logic.
The article further demonstrates how only a design-based framework reveals the higher-level organization of biological systems.
SysML consists of nine diagrams that map a system’s structure, behavior, requirements, and parameters. Each diagram highlights a different facet of a complex system; together they generate insights into a system’s design logic and operations. Johansen incorporated SysML into a methodology he developed to reverse engineer biological systems, which he called Reverse-Engineering Object-Oriented Systems Engineering Method (RE-OOSEM). The methodology incudes six elements:
“(1) Survey academic articles and textbook sources … (2) Capture the descriptive information … (3) Convert the descriptive information summary into prescriptive engineering information for architecture capture. … (4) Generate a high-level functional architecture that maps the prescriptive information to function. … (5) Capture the system architectural details into as many SysML diagrams as necessary … (6) Evaluate the system architecture and fuse information from various SysML diagrams.”
Johansen’s application of RE-OOSEM to chemotaxis yielded several insights:
“The results show the following engineering perspective observations.
(1) Several control components are not dedicated but are available and utilized when needed.
(2) Individual chemoreceptors act together as a sensor array.
(3) Phosphate groups act as a signaling mechanism.
(4) Methylation via CH 3 groups of the chemoreceptor results in sensitivity adaptation.
(5) Closed-loop control collaboratively utilizes ligand bonding, phosphorylation, and methylation.
(6) Timing relationships of the control subprocesses give insight into the system’s architecture.”
Johansen described how future research could model chemotaxis in diverse species to extract the engineering principles behind the differences between different chemotactic systems. It could also incorporate additional mathematical modeling and simulations to “bring further realism to how the chemotaxis process operates and why.” Johansen’s methodology will prove a valuable tool for future research into other biological systems.
“What do you think was responsible for the Cambrian explosion?”
“An Evolution Bomb”
A mutation can be beneficial, neutral, or deleterious.
Re: possible Amino Acid sequences 147 AAs long, the overwhelming percentage are nonfunctional, and a miniscule fraction are functional.
How did mutation + natural selection arrive at a functional hemoglobin subunit beta AA sequence?
James D. Johansen, “Bacterial chemotaxis control process analysis with SysML” (7 March 2024)
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This paper looks at the bacteria chemotaxis control process utilizing the System Modeling Language (SysML) to leverage well-defined and proven engineering tools for architecting, analyzing, and refining complex systems.
It proposes a new methodology called reverse-engineering object-oriented systems engineering method (RE-OOSEM) that converts descriptive biology research information into descriptive systems engineering information.
It utilizes SysML and model-based systems engineering (MBSE) to capture system architecture from biological system knowledge and inputs them into systems engineering tools.
From an engineering point of view, this allows greater insight into how biological systems operate and suggests how much model detail is required to uncover a top-down system understanding. RE-OOSEM methodology guides the SysML chemotaxis control capture process.
SysML syntax is used instead of biological syntax to facilitate biological chemotaxis control system analysis from an engineered system point of view.
The model can act as a scaffolding to help uncover system function, the relationships of system components and processes, and bioinformatic phenotype and genotype correlation.
An executable MathWorks Stateflow chemotaxis control process model based on the SysML architectural model is included.
The results show the following engineering perspective observations.
(1) Several control components are not dedicated but are available and utilized when needed.
(2) Individual chemoreceptors act together as a sensor array.
(3) Phosphate groups act as a signaling mechanism.
(4) Methylation via CH3 groups of the chemoreceptor results in sensitivity adaptation.
(5) Closed-loop control collaboratively utilizes ligand bonding, phosphorylation, and methylation.
(6) Timing relationships of the control subprocesses give insight into the system’s architecture.
…
Through biological system research and diagram development, SysML summarizes system architecture and informs researchers about gaps and potential places to do follow-up work.
Engineers are familiar with SysML, so it allows for collaborations with biologists using tools they know.
SysML focuses on aspects of a system from multiple vantage points with different diagram types.
OPM may be easier for biologists to utilize and share with engineers.
Here is a summary of sample systems biology colleague research with references from their primary discipline.
As mentioned earlier, Schulz did a three-part engineering characterization of the bacterial flagellum.
He explores biology and engineering concepts in a systems biology context.^1, 27, 28
Brown^33 and Haupt^34 are exploring glycolysis from a systems biology point of view.
Bergen included systems biology perspectives in assessing genetics and molecular biology systems.^35-37
…
Several engineering observations were made about the control process from the architectural model.
(1) The chemotaxis control components are available as needed instead of being hard-wired like system components in electronic devices like cell phones, which typically cannot be replaced.
(2) Chemoreceptors bond with a ligand for some time and then release it, making it ready to sense the concentration again.
This conceptually is like a single pixel in a camera focal plane array that passes on a signal when a photon impacts it.
(3) The phosphorylation process uses phosphate groups that can be passed around the CheA, CheY, and CheB components in a fashion that conceptually can be thought of as an electronic current.
…
CONCLUSIONS
RE-OOSEM is beneficial to both biologists and engineers.
SysML Models can be developed at a high level to capture functional capability.
Details can be added as needed to answer specific research questions.
_For biologists_, RE-OOSEM with SysML frames how biological systems operate from behavioral processes (e.g., ACT), and structural, other behavioral, requirements, and parameter constraints points of view.
SysML emphasizes architectural modeling and implementation assessment. Examining systems via model structure focuses on where to invest time and resources.
_For engineers_, RE-OOSEM with SysML modeling can improve the overall understanding of biological systems and potentially apply these approaches to human-engineered systems.
David, here is–I think–the biggest reason that most people who know anything about it don’t take ID seriously.
It is *perfectly normal* for a scientific theory to have things it can’t explain. That is where scientific research generally focuses; solving those unsolved problems, ironing out the remaining wrinkles.
Max Planck was famously discouraged from going into physics because, he was told, all the hard problems had been solved and there were only a few loose ends left to tie up. Yet, in working on one of those last nagging problems–where the existing models didn’t predict the observed behavior–(the UV catastrophe), he accidentally stumbled onto a huge leap towards inventing QM.
Today, GR is known not to work in certain contexts. Physicists argue about how to fix it, but very few want to throw it out and start over because it has been insanely successful, in terms of making novel predictions that proved correct. And it has a lot of explanatory power: It lets us make sense of a lot of things that are otherwise mystifying.
Evolution has also been insanely successful in making predictions. As we learn more, we keep finding further confirmation of the theory. One of my favorite examples of the predictive power of the theory of evolution is the discovery of ** you do not have permission to see this link ** in 2004. The paleontologists knew there needed to be a certain missing link between fish and quardupeds. They knew generally what it should look like, what habitat it lived in, and when it must have lived. So they knew what sort of rock formations it might be preserved in. Then they went and started digging in those formations, and after several seasons, they found the damned thing. That is remarkable predictive power. Really think about that: “If you dig in these rocks, you’ll find fossils of a creature with these features that no one has ever seen before.” And it is only one example.
It also has a lot of explanatory power. Evolution also lets us make sense of a lot of an innumerable set of otherwise baffling things we find in the world of living things.
So on the one hand, when the ID apologist comes in ans says we should reject evolution because there are things that it doesn’t neatly explain or that it can’t (yet) account for in detail, everyone else shrugs his shoulders because that is completely normal for any scientific theory. Science isn’t done; we expect there to still be unanswered mysteries. Those explanatory holes don’t overturn the power the theory has demonstrated.
Predictive power and explanatory value are the hallmarks of good theories. A theory that has both in spades isn’t going to be jettisoned quickly. People aren’t going to give up a theory that offers so much without replacement that at the very least can promise to do at least as much. But what predictive power does ID have? What explanatory power does it have? ID apologists themselves recognize that ID doesn’t even constitute a theory. It makes no predictions. It explains nothing. Why would anyone give up a theory that explains so much, to embrace a theory that explains nothing?
The fact that the ID apologists have a track record of misrepresenting things only confirms to the rest of us that they aren’t really interested in doing science.
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Richard S. Gunasekera, Komal K. B. Raja, Suresh Hewapathirana, Emanuel Tundrea, Vinodh Gunasekera, Thushara Galbadage, and Paul A. Nelson, “ORFanID: A web-based search engine for the discovery and identification of orphan and taxonomically restricted genes,” PLOS One, 18 (10): e0291260 (2023).
Evolutionary explanations for the origin of new genes hold that genes often originate when some ancestral gene duplicates, and then those duplicates slowly diverge in sequence over time to form new gene sequences with new functions.
This evolutionary “duplication and divergence model” therefore predicts the existence of “orthologous” genes — genes with similar sequences that represent close relatives descended from common ancestral genes.
But what if a gene sequence is unique and shows no sequence similarity to any other gene? How would the duplication and divergence model explain the evolutionary origin of such a gene?
Orphan or “ORFan” genes represent precisely such genes which have amino acid sequences that resemble no other known gene.
This paper, authored by a team of scientists including ID theorists Paul Nelson and Richard Gunasekera, reports an ID-funded project that is exploring the nature and origin of orphan genes:
“With the numerous genomes sequenced today, it has been revealed that a noteworthy percentage of genes in a given taxon of organisms in the phylogenetic tree of life do not have orthologous sequences in other taxa.
These sequences are commonly referred to as ‘orphans’ or ‘ORFans’ if found as single occurrences in a single species or as ‘taxonomically restricted genes’ (TRGs) when found at higher taxonomic levels.
Quantitative and collective studies of these genes are necessary for understanding their biological origins.”
The article explains that orphan genes are not rare, and in fact make up “large fractions” of the genomes of many species, meaning “TRGs represent important mediators of phenotypic novelty.”
The prevalence of orphan genes has implications for evolutionary models of the origin of new genes, since these models predict “we should see a connection” between the gene sequences of related genes.
The paper notes, however, that the study of orphan genes has largely been neglected because they were poorly understood — presumably also because they did not fit standard evolutionary models:
“The neglect of orphans has continued to some extent in the genomic era, as functional roles are mainly assigned to newly sequenced genes mainly via homology criteria (e.g., existing annotations in other species).
However, it has been shown in some cases that orphan genes are uniquely involved in making one species distinct from another phenotypically.”
The project announced in this paper aims to correct the neglect of orphan genes by presenting a new online tool, ORFanID, for searching genome databases to identify and catalogue orphan genes.
Reflecting this neglect, the paper notes that existing bioinformatics tools “are not suited to identify orphans as ORFanID is designed to do.”
ORFanID is distinct because it not only identifies orphan genes but connects to a database cataloguing orphan genes across many species which can be used by future researchers who wish to engage in large-scale investigations of orphan genes:
“ORFanID’s distinctiveness is in three aspects:
(1) It processes not just protein/amino acid sequences but also DNA/nucleotide sequences.
(2) With its built-in homology interpreter and classifier, this search engine provides the taxonomic rank of a gene either as an orphan gene or as a gene restricted to a taxonomic level in the tree of life;
(3) As ORFans and TRGs are identified, ORFanID builds its own database with the results of the analysis and provides the researcher with the possibility to further explore the data.”
Orphan genes / TRGs are of great interest to the design hypotheses.
Evolutionary models require material templating from common ancestors whereas design allows for, and indeed predicts, the free use of all possible protein sequence space, as the immaterial designing intellect inferred by ID theory can move without limit to any point in that space and actualize it.
In other words, minds are capable of producing the precise types of informational discontinuities that we see in orphan genes.
The results of this project therefore have the potential for major positive implications for intelligent design.
The paper notes that
“These findings can lead to the creation of databases of these clandestine genes that have been pre-identified at the various taxonomic levels by ORFanID, resulting in a deeper understanding of the purpose of orphan genes, their function in genomes, and their potential impact on life.”
This project thus not only has the potential to provide powerful evidence for design but also to further our understanding of orphan genes and what makes species (or taxa) unique.
“It is *perfectly normal* for a scientific theory to have things it can’t explain”
Can Darwin’s theory of natural selection explain the:
origin of ‘species’?
origin of new biological structures having novel functions?
origin of the massive quantity of information encoded in biology’s DNA?
fossil record’s pattern of abrupt appearances followed by stasis?
Can “the theory of evolution” explain the origination of the 1st biological lifeform?
“Today, GR is known not to work in certain contexts”
Such as where?
“examples of the predictive power of the theory of evolution is the discovery of Tiktaalik in 2004.
The paleontologists knew there needed to be a certain missing link between fish and quardupeds.
They knew generally what it should look like, what habitat it lived in, and when it must have lived.
So they knew what sort of rock formations it might be preserved in.
Then they went and started digging in those formations, and after several seasons, they found the damned thing.
That is remarkable predictive power.
Really think about that: ‘If you dig in these rocks, you’ll find fossils of a creature with these features that no one has ever seen before.'”
Between what fish and what “quarduped” is Tiktaalik a “missing link”?
Does “the theory of evolution” predict Archaeopteryx?
“Evolution also lets us make sense of a lot of an innumerable set of otherwise baffling things we find in the world of living things”
Does “evolution… make sense of” how come the giraffe has such a long neck?
“when the ID apologist comes in ans says we should reject evolution because there are things that it doesn’t neatly explain or that it can’t (yet) account for in detail”
Meaning of “evolution”?
“…ID doesn’t even constitute a theory.
It makes no predictions.
It explains nothing”
Does “the theory of evolution” predict that there are such things as:
‘junk DNA’?
vestigial organs?
“am asking for a quotation from the actual article–the text that passed peer review and got published–that supports ID”
I don’t know how this supports ID.
Also, I don’t know enough biology to assess whether ORFans do or don’t undercut Darwin’s theory of natural selection.
ORFanID: A web-based search engine for the discovery and identification of orphan and taxonomically restricted genes (October 25, 2023)
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With the numerous genomes sequenced today, it has been revealed that a noteworthy percentage of genes in a given taxon of organisms in the phylogenetic tree of life do not have orthologous sequences in other taxa.
These sequences are commonly referred to as “orphans” or “ORFans” if found as single occurrences in a single species or as “taxonomically restricted genes” (TRGs) when found at higher taxonomic levels.
Pity the Unwanted Orphan Genes — An Awkward Topic for Darwinism
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…[Paul] Nelson elaborates on the challenge to Darwinian theory from so-called orphan genes.
These are DNA sequences coding for protein (in the context of this discussion) with no known genetic relatives. They exist in great numbers. They often serve in vital roles in organisms. Where did they come from? Darwinism assumes a relationship of cousinship not only among all creatures, past and present, but between gene sequences. Orphan genes defy the theory of cousinship.
The history of life, presumed to originate with LUCA (“Last Universal Common Ancestor”), doesn’t afford enough time to generate these novelties, seemingly out of nowhere. On the other hand, a perspective open to intelligent design accommodates the possibility of generating absolutely new biological information as needed, at, so to speak, the designer’s pleasure. This information could occur anywhere at all in possible genetic sequence space.
Darwinism has its possible rationalizations of the orphan genes problem. It’s always does. But rationalizations are all they are.
Orphan genes are another example where predictions of standard evolutionary theory are defeated by the evidence. Meanwhile ID takes the evidence in stride. As a scientific theory, Darwinian evolution is indeed testable, except that it fails its tests.
the interview
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The evolutionary mystery of orphan genes
Every newly sequenced genome contains genes with no traceable evolutionary descent – the ash genome was no exception
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This week in Nature I and my co-authors published the ash tree genome. Within it we found 38,852 protein-coding genes. Of these one quarter (9,604) were unique to ash. On the basis of our research so far, I cannot suggest shared evolutionary ancestry for these genes with those in ten other plants we compared ash to: coffee, grape, loblolly pine, monkey flower, poplar, tomato, Amborella, Arabidopsis, barrel medic, and bladderwort. This is despite the fact that monkey flower and bladderwort are in the same taxonomic order (Lamiales) as ash.
Such genes are often known as “orphan genes” – orphans because they appear to be lacking evolutionary parents. A more precise term is “taxonomically restricted genes” as this allows us to specify the taxonomic level at which they are unique. Some of the 9,604 genes we found to be unique to ash will be unique to the species, some unique to the genus, and some to the family. On further research, some may turn out not to be orphans at all. In future we plan to conduct detailed comparisons with other ash species and with olive, which is in the same family as ash.
Orphan genes are found every time a new genome is sequenced. Their ubiquity has been one of the biggest surprises of genomics over the last 20 years. Many researchers had hypothesised that the number of orphan genes found would steadily diminish as more and more genomes were sequenced – but this is not the case. Orphan genes continue to comprise a sizeable proportion of each new genome sequenced. I and Paul Nelson reviewed this topic in a chapter of a book published this year by Cambridge University Press: “Next Generation Systematics”.
Orphan genes are “the hard problem” for evolutionary genomics. Because we can’t find other genes similar to them in other species, we can’t build family trees for them. We cannot hypothesise their gradual evolution; instead they seem to appear out of nowhere. Various attempts have been made at explaining their origins but – as Paul and I describe in our book chapter – the problem remains unsolved.
Give their ubiquity in all genome sequences orphan genes receive comparatively little attention from the research community. I suspect this is partly because they are such a difficult problem. Science is “the art of the soluble”. It may be that little funding finds its way to the origin of orphan genes because it appears to be an insoluble problem.
Popularisers and communicators of science have also had surprisingly little to say about orphan genes. This is a pity: what can be more interesting and more inspiring than an unsolved mystery? Who could choose to ignore a lost orphan?
“Evolution also lets us make sense of a lot of an innumerable set of otherwise baffling things we find in the world of living things”
Do you consider the answer below to the question posed below to be adequate and satisfactory?
AI response to
According to evolutionary theory, how did the giraffe get its long neck?
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According to evolutionary theory, the giraffe’s long neck evolved through a gradual process of natural selection.
It is not a single adaptation for feeding on high leaves, but rather a complex trait influenced by multiple factors.
Initial Advantage: Fossil evidence suggests that giraffe ancestors had shorter necks, and the long-necked trait emerged over time.
The earliest known giraffe fossils date back to the late Miocene epoch, around 10-12 million years ago.
Competition and Adaptation: As giraffe populations competed for resources, individuals with slightly longer necks may have had a selective advantage.
This could have been due to their ability to:
Reach higher branches for food, as suggested by some theories.
Engage in agonistic behaviors, such as neck-wrestling, to establish dominance and mating opportunities, as proposed by recent studies.
Iterative Selection: Over generations, the genetic variation for longer necks became more prevalent as individuals with this trait were more likely to survive, reproduce, and pass on their advantageous characteristics to their offspring.
Co-evolution with Other Traits: The evolution of the giraffe’s long neck was likely linked to changes in other body parts, such as the development of stronger neck and leg muscles, as well as modifications to the skull and vertebrae.
In summary, the giraffe’s long neck is not solely an adaptation for feeding, but rather a complex trait shaped by a combination of factors, including competition, agonistic behaviors, and co-evolution with other body parts.
“Evolution also lets us make sense of a lot of an innumerable set of otherwise baffling things we find in the world of living things”
Do you consider adequate & satisfactory the answer below to the question posed below?
AI response to
According to evolutionary theory, how did eyes appear?
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According to evolutionary theory, eyes likely evolved from light-sensitive patches or spots on ancient organisms.
These early photoreceptors allowed cells to detect changes in light intensity, enabling simple responses to environmental cues.
Four Stages in Vertebrate Eye Evolution
Biologist D.E. Nilsson independently proposed four general stages in the evolution of a vertebrate eye from a patch of photoreceptors:
Light-sensitive patches: Initial light detection through simple, non-image-forming photoreceptors.
Pigment spots: Concentration of photoreceptors into small areas, allowing for basic directionality and intensity detection.
Ommatidia: Development of small, light-guiding structures (ommatidia) containing multiple photoreceptors, similar to those found in modern-day insects and crustaceans.
Complex eyes: Evolution of lenses, pupils, and other structures to focus and regulate light, enabling image formation and more sophisticated vision.
Fossil Record and Cambrian Explosion
Fossil evidence suggests that the first possible eyes appeared around 555 million years ago during the Ediacaran period.
The oldest certain fossilized eye is from a Schmidtiellus reetae fossil from 530 million years ago, exhibiting a structure similar to compound eyes found in modern-day insects and bees.
The Cambrian explosion, a period of rapid evolution around 541 million years ago, saw the emergence of many animal phyla, including those with complex eyes.
The “Light Switch” theory proposes that the evolution of advanced eyes triggered an arms race, driving further evolutionary innovation.
Common Molecular Toolkit
Despite diverse eye structures, all eyes share a common molecular “toolkit” for building an eye.
This toolkit includes basic components, such as photopigments and signaling pathways, which have been co-opted and modified throughout evolution to create the wide range of eye forms and functions seen today.
“Evolution also lets us make sense of a lot of an innumerable set of otherwise baffling things we find in the world of living things”
Excluding the IC element, do you consider adequate & satisfactory the answer below to the question posed below?
AI response to
According to evolutionary theory, how did peacock feathers and their distinctive pattern appear?
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According to evolutionary theory, the distinctive pattern on peacock feathers evolved through a gradual process of genetic variation, natural selection, and sexual selection.
Here’s a summary of the key points:
Initial Variation: Peacocks’ ancestors likely had simpler, more uniform feathers. Over time, genetic mutations introduced variations in color, shape, and pattern.
Sexual Selection: Female peahens, seeking mates with desirable traits, favored males with more elaborate and attractive plumage. This led to the selection of males with increasingly complex and vibrant feathers.
Gradual Accumulation: Through repeated cycles of genetic variation, natural selection, and sexual selection, the peacock’s tail feathers accumulated multiple features, including:
Coloration (e.g., iridescent blues and greens)
Pattern elements (e.g., eyespots, stripes)
Shape and structure (e.g., long, slender feathers)
Irreducible Complexity [!] : The final pattern and structure of the peacock’s tail feathers exhibit irreducible complexity, meaning that removing or simplifying any single feature would compromise the overall aesthetic appeal.
Estimated Genetic Requirements: Evolutionists estimate that around 20 genes may be required to produce the intricate pattern and coloration of a single peacock feather, although this number may be conservative.
In summary, the distinctive pattern on peacock feathers evolved through a gradual process of genetic variation, natural selection, and sexual selection, driven by the preferences of female peahens for males with more elaborate and attractive plumage.
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