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Defending the Christian Worldview, Creationism, and Intelligent Design

This is my personal virtual library, where i collect information, which leads in my view to the Christian faith, creationism, and Intelligent Design as the best explanation of the origin of the physical Universe, life, and biodiversity


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Defending the Christian Worldview, Creationism, and Intelligent Design » Intelligent Design » Information Theory, Coded Information in the cell » The algorithmic origins of life

The algorithmic origins of life

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1The algorithmic origins of life Empty The algorithmic origins of life Wed Nov 04, 2020 6:23 pm

Otangelo


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The algorithmic origins of life

https://reasonandscience.catsboard.com/t3061-the-algorithmic-origins-of-life

1. Creating a recipe to make a cake is always a mental process. Creating a blueprint to make a machine is always a mental process.
2. To suggest that a physical process can create instructional assembly information, a recipe or a blueprint, is like suggesting that a throwing ink on paper will create a blueprint. It is never going to happen!  
3. Physics and chemistry alone do not possess the tools to create a concept, or functional complex machines made of interlocked parts for specific purposes
4. The only cause capable of creating conceptual semiotic information is a conscious intelligent mind.
5. DNA stores codified information to make proteins, and cells, which are chemical factories in a literal sense.


https://biosemiosis.net/?fbclid=IwAR1xTZ-JWsSeSaTHqN5MmsaXpPN6dlFQz4liWCcOYzt6ugib-TVWv9y8YIE
Information is not a tangible entity, it has no energy and no mass, it is not physical,  it is conceptual.

- Life is a software/information-driven process.
- Information is not physical it is conceptual.
- The only known source of semiotic information is prior to intelligence.
- Life is therefore the direct product of a deliberate creative intellectual process.

Semiotic functional information is not a tangible entity, and as such, it is beyond the reach of, and cannot be created by any undirected physical process.
This is not an argument about probability. Conceptual semiotic information is simply beyond the sphere of influence of any undirected physical process. To suggest that a physical process can create semiotic code is like suggesting that a rainbow can write poetry... it is never going to happen!  Physics and chemistry alone do not possess the tools to create a concept. The only cause capable of creating conceptual semiotic information is a conscious intelligent mind.
Life is no accident, the vast quantity of semiotic information in life provides powerful positive evidence that we have been designed.
To quote one scientist working at the cutting edge of our understanding of the programming information in biology, he described what he saw as an “alien technology written by an engineer a million times smarter than us”

If you convert the idea to a sentence to communicate (as I do here) or to remember it, that sentence may be physical, yet is dependent upon the non-physical idea, which is in no way dependent upon it.

Information is not physical
https://arxiv.org/pdf/1402.2414.pdf
Information  is a disembodied abstract entity independent of its physical carrier. ”Information is always tied to a physical representation. It is represented by engraving on a stone tablet, a spin, a charge, a hole in a punched card, a mark on paper, or some other equivalent. This ties the handling of information to all the possibilities and restrictions of our real physical word, its laws of physics and its storehouse”. However, the legitimate questions concern the physical properties of information carriers like ”stone tablet, a spin, a charge, a hole in a punched card, a mark on paper”, but not the information itself.  Information is neither classical nor quantum, it is independent of the properties of physical systems used to its processing.

An algorithm is a finite sequence of well-defined, computer-implementable instructions resulting in precise intended functions. A prescriptive algorithm in biological context can be described as performing control operations using  rules, axioms and coherent instructions. These instructions are performed, using a linear, digital, cybernetic string of symbols representing syntactic, semantic and pragmatic prescriptive information. 


Cells host algorithmic programs for cell division, cell death, enzymes pre-programmed to perform DNA splicing, programs for dynamic changes of gene expression in response to the changing environment. Cells use pre-programmed adaptive responses to genomic stress,  pre-programmed genes for fetal development regulation, temporal programs for genome replication, pre-programmed animal genes dictating behaviors including reflexes and fixed action patterns, pre-programmed biological timetables for aging etc.

A programming algorithm is like a recipe that describes the exact steps needed to solve a problem or reach a goal. We've all seen food recipes - they list the ingredients needed and a set of steps for how to make a meal. Well, an algorithm is just like that.  A programming algorithm describes how to do something, and it will be done exactly that way every time.

Okay, you probably wish you could see an example, how that works in the cell, right? Lets make an analogy. Lets suppose you have a receipe to make spaghetti with a special tomato sauce written on a word document saved on your computer.  You have a japanese friend, and only communicate with him using the google translation program. Now he wants to try out that receipe, and asks you to send him a copy. So you write an email, annex the word document, and send it to him. When he receives it, he will use google translate, and get the receipe in japanese, written in kanji, in logographic japanese characters which he understands. With the information at hand, he can make the spaghetti  with that fine special tomato souce exactly as described in the receipe. In order for that communication to happen, you use at your end 26 letters from the alphabet to write the receipe, and your friend has 2,136 kanji characters that permits him to understand the receipe in Japanese. Google translate does the translation work.

While the receipe is written on a word document saved on your computer, in the cell, the receipe (instructions or master plan) for the construction of proteins which are the life essential molecular machines, veritable working horses, is written in genes through DNA. While you use the 26 letters of the alphabet to write your receipe, the Cell uses DNA, deoxyribonucleotides, four monomer "letters". In kanji there are 2136 characters, the alphabet uses 26,   computer codes being binary, use 0,1. The language of DNA is digital, but not binary. Where binary encoding has 0 and 1 to work with (2 - hence the 'bi'nary)  DNA uses four different organic bases, which are adenine (A), guanine (G), cytosine (C) and thymine (T)

The way by which DNA stores the genetic information consists of codons equivalent to words, consisting of an array of three DNA nucleotides. These triplets form "words". While you used sentences to write the spaghetti receipt, the equivalent sentences are  called genes written through codon "words", . With four possible nucleobases, the three nucleotides can give 4^3 = 64 different possible "words" (tri-nucleotide sequences). In the standard genetic code, three of these 64 codons (UAA, UAG and UGA) are stop codons.

There has to be a mechanism to extract the information in the genome, and send it to the ribosome,  the factory that makes proteins, which is at another place in the cell, free floating in the cytoplasm. The message contained in the genome is transcribed by a very complex molecular machine, called RNA polymerase. It makes a transcript, a copy of the message in the genome, and that transcript is sent to the Ribosome. That transcript is called messenger RNA or typically mRNA. 

In communications and information processing, code is a system of rules to convert information—such as assigning the meaning of a letter, word, into another form, ( as another word, letter, etc. ) In translation, 64 genetic codons are assigned to 20 amino acids. It refers to the assignment of the codons to the amino acids, thus being the cornerstone template underling the translation process. Assignment means designating, ascribing, corresponding, correlating.
  
The Ribosome does basically what google translate does. But while google translate just gives the receipt in another language, and our japanese friend still has to make the spaghettis,  the Ribosome actually makes in one step the end product, which are proteins. 

Imagine the brainpower involved in the entire process from inventing the receipt to make spaghettis, until they are on the table of your japanese friend. What is involved ?
 
1. Your imagination of the receipt
2. Inventing an alphabet, a language
3. Inventing the medium to write down the message
4. Inventing the medium to store the message
5. Storing the message in the medium
6. Inventing the medium to extract  the message
7. Inventing the medium to send the message
8. Inventing the second language ( japanese)
9. Inventing the translation code/cipher from your language, to japanese
10. Making the machine that performs the translation
11. Programming the machine to know both languages, to make the translation
12. Making the translation
12. Makin of the spaghettis on the other end using the receipt in japanese  

1. Cells host Genetic information
2. This information prescribes functional outcomes due to the right particular specified complex sequence of triplet codons and ultimately the translated sequencing of amino acid building blocks into protein strings.  The sequencing of nucleotides in DNA also prescribes highly specific regulatory micro RNAs and other epigenetic factors.
3. Algorithms, prescribing functional instructions, digital programming, using symbols and coding systems are abstract respresentations and non-physical, and originate always from thought—from conscious or intelligent activity. 
4. Therefore, genetic and epigenetic information comes from an intelligent mind. Since there was no human mind present to create life, it must have been a supernatural agency.

1. Algorithms, prescribing functional instructions, digital programming, using symbols and coding systems are abstract respresentations and non-physical, and originate always from thought—from conscious or intelligent activity. 
2. Genetic and epigenetic information is characterized containing prescriptive codified information, which result in functional outcomes due to the right particular specified complex sequence of triplet codons and ultimately the translated sequencing of amino acid building blocks into protein strings.  The sequencing of nucleotides in DNA also prescribes highly specific regulatory micro RNAs and other epigenetic factors.
3. Therefore, genetic and epigenetic information comes from an intelligent mind. Since there was no human mind present to create life, it must have been a supernatural agency.

Three subsets of sequence complexity and their relevance to biopolymeric information
https://link.springer.com/article/10.1186/1742-4682-2-29
An algorithm is a finite sequence of well-defined, computer-implementable instructions. Genetic algorithms instruct sophisticated biological organization. Three qualitative kinds of sequence complexity exist: random (RSC), ordered (OSC), and functional (FSC). FSC alone provides algorithmic instruction.  A linear, digital, cybernetic string of symbols representing syntactic, semantic and pragmatic prescription; each successive sign in the string is a representation of a decision-node configurable switch-setting – a specific selection for function. Selection, specification, or signification of certain "choices" in FSC sequences results only from nonrandom selection.

Nucleotides are grouped into triplet Hamming block codes, each of which represents a certain amino acid. No direct physicochemical causative link exists between codon and its symbolized amino acid in the physical translative machinery. Physics and chemistry do not explain why the "correct" amino acid lies at the opposite end of tRNA from the appropriate anticodon. Physics and chemistry do not explain how the appropriate aminoacyl tRNA synthetase joins a specific amino acid only to a tRNA with the correct anticodon on its opposite end. Genes are not analogous to messages; genes are messages. Genes are literal programs. They are sent from a source by a transmitter through a channel.   Prescriptive sequences are called "instructions" and "programs." They are not merely complex sequences. They are algorithmically complex sequences. They are cybernetic.

Leroy Hood  The digital code of DNA   23 January 2003
The discovery of the double helix in 1953 immediately raised questions about how biological information is encoded in DNA. A remarkable feature of the structure is that DNA can accommodate almost any sequence of base pairs — any combination of the bases adenine (A), cytosine (C), guanine (G) and thymine (T) — and, hence any digital message or information. 
https://www.nature.com/articles/nature01410

Translation occurs after the messenger RNA (mRNA) has carried the transcribed ‘message’ from the DNA to protein-making factories in the cell, called ribosomes?.
The message carried by the mRNA is read by a carrier molecule called transfer RNA ?(tRNA).
https://www.yourgenome.org/facts/what-is-gene-expression


The capabilities of chaos and complexity.
http://europepmc.org/article/PMC/2662469
Do symbol systems exist outside of human minds?
Molecular biology’s two-dimensional complexity (secondary biopolymeric structure) and three-dimensional complexity (tertiary biopolymeric structure) are both ultimately determined by linear sequence complexity (primary structure; functional sequence complexity, FSC).  The codon table is arbitrary and formal, not physical. The linking of each tRNA with the correct amino acid depends entirely upon on a completely independent family of tRNA aminoacyl synthetase proteins. Each of these synthetases must be specifically prescribed by separate linear digital programming, but using the same MSS. These symbol and coding systems not only predate human existence, they produced humans along with their anthropocentric minds.


The algorithmic origins of life Ijms-10-00247f3
The image above shows the prescriptive coding of a section of DNA. Each letter represents a choice from an alphabet of four options. The particular sequencing of letter choices prescribes the sequence of triplet codons and ultimately the translated sequencing of amino acid building blocks into protein strings.  The sequencing of nucleotides in DNA also prescribes highly specific regulatory micro RNAs and other epigenetic factors. Thus linear digital instructions program cooperative and holistic metabolic proficiency.

Chaos is neither organized nor a true system, let alone “self-organized.” A bona fide system requires organization. Chaos by definition lacks organization.  What formal functions does for example a hurricane perform? It doesn’t DO anything constructive or formally functional because it contains no formal organizational components. It has no programming talents or creative instincts. A hurricane is not a participant in Decision Theory. A hurricane does not set logic gates according to arbitrary rules of inference. A hurricane has no specifically designed dynamically-decoupled configurable switches. No means exists to instantiate formal choices or function into physicality. A highly self-ordered hurricane does nothing but destroy organization. That applies to any unguided, random, natural events. 

The capabilities of stand-alone chaos, complexity, self-ordered states, natural attractors, fractals, drunken walks, complex adaptive systems, and other subjects of non linear dynamic models are often inflated. Scientific mechanism must be provided for how purely physicodynamic phenomena can program decision nodes, optimize algorithms, set configurable switches so as to achieve integrated circuits, achieve computational halting, and organize otherwise unrelated chemical reactions into a protometabolism. We know only of conscious or intelligent agents able to provide such things. 


Information and the Nature of Reality From Physics to Metaphysics page 149
The concept of information has been a victim of a philosophical impasse that has a long and contentious history: the problem of specifying the ontological status of the representations or contents of our thoughts. How can the
content (aka meaning, reference, significant aboutness) of a sign or thought have any causal efficacy in the world if it is by definition not intrinsic to whatever physical object or process represents it?

Consider the classic example of a wax impression left by a signet ring in wax. Except for the mind that interprets it, the wax impression is just wax, the ring is just a metallic form, and their conjunction at a time when the wax was still warm and malleable was just a physical event in which one object alters another when they are brought into contact. Something more makes the wax impression a sign that conveys information. It must be interpreted by someone.

In order to develop a full scientific understanding of information we will be required to give up thinking about it, even metaphorically, as some artifact or commodity. To make sense of the implicit representational function that distinguishes information from other merely physical relationships, we will need to find a precise way to characterize its defining nonintrinsic feature – its referential content – and show how it can be causally efficacious despite its physical absence. The enigmatic status of this relationship was eloquently, if enigmatically, framed by Brentano’s use of the term “inexistence” when describing mental phenomena.

Signature in the Cell, Stephen Meyer page 16
What humans recognize as information certainly originates from thought—from conscious or intelligent activity. A message received via fax by one person first arose as an idea in the mind of another. The software stored and sold on a compact disc resulted from the design of a software engineer. The great works of literature began first as ideas in the minds of writers—Tolstoy, Austen, or Donne. Our experience of the world shows that what we recognize as information invariably reflects the prior activity of conscious and intelligent persons.

We now know that we do not just create information in our own technology; we also find it in our biology—and, indeed, in the cells of every living organism on earth. But how did this information arise? The age-old conflict between the mind-first and matter-first world-views cuts right through the heart of the mystery of life’s origin. Can the origin of life be explained purely by reference to material processes such as undirected chemical reactions or random collisions of molecules?


The algorithmic origins of life
https://royalsocietypublishing.org/doi/full/10.1098/rsif.2012.0869
The key distinction between the origin of life and other ‘emergent’ transitions is the onset of distributed information control, enabling context-dependent causation, where an abstract and non-physical systemic entity (algorithmic information) effectively becomes a causal agent capable of manipulating its material substrate.

Biological information is functional due to the right sequence. There have been a variety of terms employed for measuring functional biological information — complex and specified information (CSI), Functional Sequence Complexity (FSC) Instructional complex Information.  I like the term instructional because it defines accurately what is being done, namely instructing the right sequence of amino acids to make proteins, and also the sequence of messenger RNA, which is used for gene regulation, and a variety of yet unexplored function.

Another term is prescriptive information (PI). It describes as well accurately what genes do. They prescribe how proteins have to be assembled. But it smuggles in as well a meaning, which is highly disputed between proponents of intelligent design, and unguided evolution. Prescribing implies that an intelligent agency preordained the nucleotide sequence in order to be functional. The following paper states:



Dichotomy in the definition of prescriptive information suggests both prescribed data and prescribed algorithms: biosemiotics applications in genomic systems
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3319427/
Biological information frequently manifests its “meaning” through instruction or actual production of formal bio-function. Such information is called Prescriptive Information (PI). PI programs organize and execute a prescribed set of choices. Closer examination of this term in cellular systems has led to a dichotomy in its definition suggesting both prescribed data and prescribed algorithms are constituents of PI. This paper looks at this dichotomy as expressed in both the genetic code and in the central dogma of protein synthesis. An example of a genetic algorithm is modeled after the ribosome, and an examination of the protein synthesis process is used to differentiate PI data from PI algorithms.

Both the method used to combine several genes together to produce a molecular machine and the operational logic of the machine are examples of an algorithm. Molecular machines are a product of several polycodon instruction sets (genes) and may be operated upon algorithmically. But what process determines what algorithm to execute?

In addition to algorithm execution, there needs to be an assembly algorithm. Any manufacturing engineer knows that nothing (in production) is built without plans that precisely define orders of operations to properly and economically assemble components to build a machine or product. There must be by necessity, an order of operations to construct biological machines. This is because biological machines are neither chaotic nor random, but are functionally coherent assemblies of proteins/RNA elements. A set of operations that govern the construction of such assemblies may exist as an algorithm which we need to discover. It details real biological processes that are operated upon by a set of rules that define the construction of biological elements both in a temporal and physical assembly sequence manner.

An Algorithm is a set of rules or procedures that precisely defines a finite sequence of operations. These instructions prescribe a computation or action that, when executed, will proceed through a finite number of well-defined states  that leads to specific outcomes.  In this context an algorithm can be represented as: Algorithm = logic + control; where the logic component expresses rules, operations, axioms and coherent instructions. These instructions may be used in the computation and control, while decision-making components determines the way in which deduction is applied to the axioms according to the rules as it applies to instructions.

A ribosome is a biological machine consisting of nearly 200 proteins (assembly factors) that assist in assembly operations, along with 4 RNA molecules and 78 ribosomal proteins that compose a mature ribosome. This complex of proteins and RNAs collectively produce a new function that is greater than the individual functionality of proteins and RNAs that compose it.

The DNA (source data), RNA (edited mRNA), large and small RNA components of ribosomal RNA, ribosomal protein, tRNA, aminoacyl-tRNA synthetase enzymes, and "manufactured" protein (ribosome output) are part of this one way, irreversible bridge contained in the central dogma of molecular biology.

One of the greatest enigmas of molecular biology is how codonic linear digital programming is not only able to anticipate what the Gibbs free energy folding will be, but it actually prescribes that eventual folding through its sequencing of amino acids. Much the same as a human engineer, the nonphysical, formal PI instantiated into linear digital codon prescription makes use of physical realities like thermodynamics to produce the needed globular molecular machines.

The functional operation of the ribosome consists of logical structures and control that obeys the rules for an algorithm. The simplest element of logical structure in an algorithm is a linear sequence. A linear sequence consists of one instruction or datum, followed immediately by another as is evident in the linear arrangement of codons that make up the genes of the DNA.

The mRNA (which is itself a product of the gene copy and editor subroutine) is a necessary input which is formatted by grammatical rules.

Top-down causation by information control: from a philosophical problem to a scientific research programme
https://sci-hub.st/https://royalsocietypublishing.org/doi/10.1098/rsif.2008.0018



Last edited by Otangelo on Fri Sep 17, 2021 7:03 pm; edited 12 times in total

https://reasonandscience.catsboard.com

2The algorithmic origins of life Empty Re: The algorithmic origins of life Wed Nov 18, 2020 11:28 am

Otangelo


Admin

1. Intelligence can and does describe reality, and objects in the real world. That's descriptive information.
2. But intelligence also structures, organizes, controls, and orders reality. That's using prescriptive information.
3. That is a quality of power - exclusive to intelligence.

How the DNA Computer Program Makes You and Me
https://www.quantamagazine.org/how-the-dna-computer-program-makes-you-and-me-20180405/


Dynamic changes of genome, pre-programmed or in response to the changing environment.
In the last decade or so, however, it has been revealed that genetic material is not stable or static but a dynamic one, changing incessantly and rapidly, the changes being either pre-programmed or in response to the changing environment.
https://agris.fao.org/agris-search/search.do;jsessionid=12397CF37F046B9EB4DEA093BC909F0B?request_locale=fr&recordID=KR19900040981&query=&sourceQuery=&sortField=&sortOrder=&agrovocString=&advQuery=&centerString=&enableField=

These alterations in the genome size occurred right at the first generation of amphidiploids, revealing the rapidity of the event. They suggest that these alterations, observed after allopolyploidization and without additive effect on the genome size, represent a pre-programmed adaptive response to the genomic stress caused by hybridization, which might have the function of stabilizing the genome of the new cell.
https://www.scielo.br/scielo.php?pid=S1413-70542003000100003&script=sci_arttext

Early pre-programming of genes
Special proteins are pre-programming genes which later regulate fetal development. This pre-programming occurs at an earlier stage than previously known.
https://partner.sciencenorway.no/dna-forskningno-norway/early-pre-programming-of-genes/1403186

[Pre-programmed genes]
https://pubmed.ncbi.nlm.nih.gov/28823208/

The evolution of the temporal program of genome replication
In yeast, active origins are distributed throughout the genome at non-transcribed and nucleosome-depleted sequences and comprise a specific DNA motif called ARS consensus sequence which is bound by the Origin Recognition Complex throughout the cell cycle 4–6. Despite of this partially pre-programmed replication activity, different cells in a population may use different subsets of active origins.
https://www.biorxiv.org/content/10.1101/210252v1.full

Learn about behaviors that are pre-programmed into an animal's genes, including reflexes and fixed action patterns.
https://www.khanacademy.org/science/ap-biology/ecology-ap/responses-to-the-environment/a/innate-behaviors

A number of theories have been generated to account for this spatial heterogeneity, including a zonated response to spatial gradients, or an internal clock where epithelial cells are pre-programmed to express different functional genes.
https://www.epistem.co.uk/spotlight/Lgr5-telocytes-signalling-source

The cells of the human body are governed by a set of pre-programmed processes, known as the cell cycle, which determines how cells progress and divide.
https://www.news-medical.net/life-sciences/The-Role-of-Cell-Division-in-Tumor-Formation.aspx

CRISPR (again, shorthand for CRISPR-Cas9), utilizes the Cas9 enzyme, a naturally produced protein in cell types built for DNA splicing, to “unzip” these chained nucleotides at a specific spot and then replace the nucleotide chain with the one attached. The location is based on pre-programmed information in the enzyme—essentially it floats around inside the nucleus until it finds the correct spot, then gets to work.
https://nanocellect.com/blog/using-crispr-technology-to-engineer-genetically-modified-cell-lines/

What are telomeres?
Are our cells just following a pre-programmed biological timetable regardless of any other factors? Most likely it’s a combination of all of these, plus some other causes we haven’t yet discovered.
https://www.science.org.au/curious/people-medicine/what-are-telomeres



https://www.sciencedirect.com/science/article/abs/pii/S0306987715003175

Dichotomy in the definition of prescriptive information suggests both prescribed data and prescribed algorithms: biosemiotics applications in genomic systems
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3319427/

"Prescriptive Information (PI)" defines the sources and nature of programming controls, regulation, and algorithmic processing. Such prescriptions are ubiquitously instantiated into all known living cells

The DNA polynucleotide molecule consists of a linear sequence of nucleotides, each representing a biological placeholder of adenine (A), cytosine (C), thymine (T) and guanine (G). This quaternary system is analogous to the base two binary scheme native to computational systems. As such, the polynucleotide sequence represents the lowest level of coded information expressed as a form of machine code.

When a functional choice of a nucleotide is  made, the polymerization of each prescriptive nucleotide into a programmed "messenger molecule" instantiates a quaternary programming choice into that syntax.

Information can be transferred from source to destination via an agreed-upon set of rules, and a language acted upon by algorithms. Each letter in the sentence "The glass contains water" is formally selected as a symbol from one of 26 alphabetical characters plus space. Each letter selection generates a simple form of Prescriptive Information (PI) as each letter contributes to forming a finite string of symbols, characterized as words having semantic meaning. PI is inherent in the selection of each letter from among 26 options even prior to the selection of words and word syntax. In both language and molecular biology synonyms occur where different letter selections can spell different words with the same semantic meaning. Sentence construction begins with letter selection.

The question becomes, are the words "the," "glass," "contains," and "water" algorithms or data? Each word is composed of a linear sequence of symbols in the form of letters, which collectively transfer a greater meaning than the individual meaning of each character. This transfer is accomplished by defining semantic meaning to a prescribed sequence of letters the intent of which is to map meaning to an arbitrary sequence of tokens. This mapping is arbitrary as evidenced by the multitude of languages that exist in our world, each language mapping "meaning" to a multitude of arbitrary sequences of symbols or tokens, be it letters, shapes or pictures. This semiotic relationship transfers into biocybernetics and biosemiotics when viewed from the biological realm

Biological information frequently manifests its "meaning" through instruction or actual production of formal bio-function. Such information is called Prescriptive Information (PI). PI programs organize and execute a prescribed set of choices. Closer examination of this term in cellular systems has led to a dichotomy in its definition suggesting both prescribed data and prescribed algorithms are constituents of PI.

Prescriptive Information (PI)
https://www.davidabel.us/papers/Prescriptive%20Information%20PI%20SciTopics.pdf

When processed, Prescriptive Information PI is used to produce formal function. Computational cybernetic programs and linguistic instructions are examples of Prescriptive Information.

Intuitive information entails syntax, semantics and pragmatics. Syntax deals with symbol sequence, various symbol associations, and related arbitrary rules of grouping. Semantics deals with the meanings represented within any symbol system. Pragmatics addresses the formal function of messages conveyed using that symbol system.

No random number generator has ever been observed to generate a meaningful message or a computational program. No physical law can determine each selection, either. If selections were dictated by law, all selections would be the same. Empirical evidence of PI arising spontaneously from inanimate nature is sorely lacking.

Particular constraints must be deliberately chosen and others rejected to steer a cause-and-effect chain towards formal pragmatic worth. The false claim is made of stochastic generation of ‘‘candidate solutions.’’ No explanation is provided as to why or how inanimate nature would prefer a solution over a non solution. . Optimization is goal-oriented and formal. Neither chance nor necessity problem-solves. Physicodynamics cannot generate ‘‘chromosomes’’ of abstract representations. The iterations are steered toward formal pragmatic success artificially by agents. The investigator pursues a goal. Evolution has no goal.  Physicochemical dynamics unaided by agent-steering has never been observed to generate formal organization. Just as pragmatic control cannot be reduced to spontaneously occurring physicodynamic constraints, arbitrarily-written rules cannot be reduced to the ‘‘necessary’’ laws of physics and chemistry. Whether we are talking about specific prescriptions or the system rules that govern those prescriptions, to talk about prescription is to talk about choice with intent at objective decision making.

We arbitrarily assign meaning to small syntactical groups of alphabetical characters, the equivalent of words. By arbitrarily, we do not mean randomly. We mean not only (1) uncoerced by determinism, but (2) deliberately chosen according to voluntarily obeyed rules, not forced laws. But how can a physical symbol vehicle, or a group of such physical symbol vehicles represent an idea in a purely materialistic world? Physicalism has never been able to answer this question. The Mind-Body problem prevails. No physical object can take on representational meaning apart from formal arbitrary assignment of abstract meaning by agents. Physicality itself cannot generate a sign/symbol/token semiotic system.


When it comes to biopolymeric syntax, semantics, and pragmatics, we fanatically insist for metaphysical reasons that the system is purely physical. No empirical, rational, or prediction-fulfillment support exists for this dogma . What determined the monomeric syntax, the sequencing, of its positive-strand template? Not chance, and not necessity. We cannot conclude that mathematics is physical just because it is instantiated into computer hardware or human brains. The same is true of genetic instruction and the PI management of life at the cellular level. Both mathematics and life are fundamentally formal. Even most epigenetic factors can be shown to be formally produced and integrated into a conceptual, cooperative, computational scheme of holistic metabolism. Life cannot exist without sophisticated, formal, genetic PI.

Semiosis, cybernetics, and formal organization all require deliberate programming decisions, not just self-ordering physicodynamic redundancy.

Three nucleotides are used to prescribe each amino acid. No physicochemical explanation exists for such sophisticated triplet codon sequencing and encryption. 

Prescriptive information requires anticipation and “choice with intent”

The biosemiosis of prescriptive information
Prescriptive information either instructs or directly produces nontrivial function at its destination.

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3The algorithmic origins of life Empty Re: The algorithmic origins of life Wed Dec 08, 2021 7:43 am

Otangelo


Admin

Claus Emmeche FROM LANGUAGE TO NATURE - the semiotic metaphor in biology 1991 1

The teleonomic character of living systems continues to challenge the conception of life prevailing among biologists. No matter how forcefully vitalistic or finalistic explanations have been defeated through developments in experimental biology such attitudes apparently never totally disappear, even among professional biologists. Rather they reappear in new guises for every new generation.

My comment: Teleonomy is the quality of apparent purposefulness and of goal-directedness of structures and functions in living organisms brought about by natural processes like natural selection. The term derives from the Greek "τελεονομία", compound of two Greek words, τέλος, from τελε-, ("end", "goal", "purpose") and νόμος nomos ("law"). Teleonomy is sometimes contrasted with teleology, where the latter is understood as a purposeful goal-directedness brought about through human or divine intention. Teleonomy is thought to derive from evolutionary history, adaptation for reproductive success, and/or the operation of a program. Teleonomy is related to programmatic or computational aspects of purpose.
https://en.wikipedia.org/wiki/Teleonomy

It is not surprising, that teleonomy is disputed by teleology. purposeful goal-directed outcomes are better explained by someone with intent and goals that brought forward certain things for specific reasons.

In the history of science controversies of this kind going on for centuries have rarely, if ever, been resolved through the unambiguous victory of one of the sides. In the first decades following the neo-Darwinistic synthesis of the 1940s, however, most biologists considered the matter settled once and for all. The purposeful character of living organisms was seen as an inevitable consequence of evolution to be causally explained by the mechanism of natural selection gradually favouring the spread of adaptive mutations within populations.

This provisional cease-fire, however, did not survive the 1970s. Severe criticism from areas ranging from paleontology to embryology and molecular biology succeeded in provoking a renewed theoretical debate on the role of natural selection in evolution, and thus the gradual and adaptive character of this process. At the deepest level, as we see it, this renewed criticism concerns the question of biological form. Is the development of form simply to be explained through the gradual improvement of function? Do organisms and parts of organisms develop their characteristic forms, just because such forms were the most functional (the most successful)?

The neo-Darwinian belief in functionality (i.e., success in reproduction) as the key to the creation of form is in fact a modern version of this substance-preference dating back to antiquity. It requires the conception of form as something to be assembled through a series of evolutionary steps, each of which would in itself be capable of passing the test for functionality. Evolutionary change of form can be seen then as divided into 'atoms of change' much in the same way as a substance may be divided into molecules. Form, in other words, is seen as a phenomenon of more or less, not as a question of the generation of qualitatively different patterns.
Opponents to this belief would claim that forms are not reducible to such a series of single steps. For instance a die of four cannot be obtained simply by adding an extra dot to a die of three. Rather quite a new pattern has to be constructed. And there would be no guarantee that the intermediate steps between two different patterns or forms would be functional at all - if anything, the opposite would seem plausible. Form, according to this view, must be considered an autonomous factor in evolution. Historical (i.e., phylogenetic), architectonical and embryological constraints would be reflected in the actual forms of living systems on this planet, and the rules governing such constraints would tell a lot more about evolution than natural selection, which can only modify the given patterns on which it works.

It is difficult to escape the feeling that much of the energy now invested in defending the functionalist image of evolution is in the end invested in order to defend a causal mechanism for evolution. Since the time of William Paley, the argument from form has always been associated with religious conceptions, whether the claim for Godly 'design' or only for the existence of vital forces or final forces. To give up natural selection as the prime mover in the world of living creatures seems identical to giving up the firm hold of science over this strange teleonomic aspect of life.

It is with this background that one must understand the temptation among biologists in recent years to consider life from the point of view of communication or information theory rather than from the point of view of classical physics and chemistry. After all, the only place to go for models of purposeful behaviour would be in the cultural sphere of the human being. And whatever the reasons for purposeful behaviour of living systems are, a more appropriate description of such behaviour might help formulating scientific explanation. The choice need not be between natural selection or vital force. Maybe a third route might be found.

This idea, of course, would probably not have been so attractive had it not been for the introduction into biology during the 1950s and 1960s of a whole set of terms borrowed from information theory. A meaningful description of the genetic processes going on at the molecular level of the cell seemed to require terms such as 'genetic code', 'messenger RNA', 'feedback', 'information', etc.

Unfortunately, in spite of their widespread use, these concepts are far from unambiguous. Thus in information theory (e.g., Shannon 1949) information is understood as an objective quantifiable entity. The information content of a message is equal to the improbability of that message. 

While this definition makes theory easy, it also removes the concept of information from any use in real life situations. In human communication statistical analysis of the probabilities to be ascribed to any definite statement is not only not feasible, it is impossible for theoretical reasons. Nobody would deny that totally unforeseen events are an essential part of life. The eventual appearance of such events obviously makes it impossible to ascribe distinct probabilities to any event. We strongly feel, nevertheless, that we often get informed through conversation. Mere improbability does not cover the real meaning of information.

In fact, most statements in human communication are only understandable at a semantic level of analysis. Evidently, the 'information' of the mathematical theory of information is a much less comprehensive category than the information exchanged between people talking.

When this concept of information is introduced into biology these sophisticated problems are imported as well. However, the tradition of biology is very unprepared to cope with such problems. Actually in the daily praxis in the laboratory information is simply identified with a substance, a piece of DNA, a gene. And in this way of confusing information with substance the new terminology of molecular genetics automatically reinforces the functionalist theory of neo-Darwinism.

We doubt that a scientific understanding of the teleonomic character of living systems will ever be possible based on this restricted concept of information. Rather we propose that biological information must be understood as embracing the semantic openness characteristic of information exchange in human communication. The cost of this, of course, is that we shall have to abandon the belief in information as an objective entity to be measured in units of bits (or genes).

In consequence, any theory which tries to describe the dynamics of living systems from the perspective of communication or exchange of signs, i.e. semiotics (from Greek: semeion = sign) would have to rely on a concept of information as a subjective category. Following Gregory Bateson we take information to mean: a difference that makes a difference to somebody. According to this definition, information is inseparable from a subject to whom this information makes sense. Our thesis is that living systems are real interpretants of information: They respond to selected differences in their surroundings. Only on this premiss, we claim, may analogies from the sphere of human communication serve as explanatory tools in the understanding of the purposeful behavior of living systems.

This of course begs the question about the significance of metaphor in science. Therefore, we first consider the nature of metaphor in science in order to distinguish between the metaphorical transfer of signification at various levels in scientific theories. Second, we focus on the metaphor of nature as language in different versions, to give an impression of the very general character and the cognitive appeal of this metaphor, and to criticize some of the models. In fact, nature perceived as language, or a language-like system, constitutes a complex web of cognate ideas of various heuristic value. In arguing for a semiotic perspective on living nature, we have to consider the existence of at least two different semiotic traditions - the linguistic structuralism of Ferdinand de Saussure, and the theory of signs of Charles S. Peirce, both of which may inspire the new view of nature. We shall argue, however, third, that the Saussurean theory as applied to living systems, raises some decisive problems in relation to an account of the different coding processes of biological information in the evolution and development of living beings in ecosystems. To spell out these problems, we shall criticize Forti's analogy between language and living species. Fourth, in the last section we show that the basic concepts of the semiotics of C. S. Peirce fit very well into the requirements of a `subjective' category of biological information (here subjective should be taken in the epistemological sense, and not as equivalent to non-rational or non-scientific). Biological structures in general and the gene in particular may be understood as signs forming a network of triadic semiotic relations through space and time.


Biosemiotics points to design

One must understand the temptation among biologists in recent years to consider life from the point of view of communication or information theory rather than from the point of view of classical physics and chemistry.

All life forms, each cell contains a description of itself stored by genes and epigenetic storage mechanisms. This description in the form of codified information furthermore must stay inactive and protected from its intra and extra-cellular milieu - until required otherwise and must be able to be faithfully replicated with a minimal number of errors, or else the description will change influenced by entropy and damage, deteriorate - and ultimately die. The function of this description is to assure the identity of the system through time. It is the memory of the living system. This description exists in the form of information stored in DNA and epigenetic storage mechanisms.

That raises the question: Why would chemicals on prebiotic earth generate a system, that self-describes itself, in digital form, and has the know-how to transform its information content into an identical representation in analog 3D form, the physical 'reality' of the actual living system, based on codified information transfer, transcription, and translation -  a system, able to decipher the DNA-code as well as to follow its instructions in a given way? Once, the 'analog phase', the message of the memory is expressed, life can flourish and perpetuate. This state of affairs sets life apart from non-life. It is a flow from sign to form.

But there have to be actually two systems of prescribed information. One that stores all the information to make the system, and a second that dictates the behavior of the system for action, responding to extra and intracellular cues, environmental conditions, nutrition demands, and energy supply. We can call them the 'replication' information, and 'interaction' information distinction. Both have to be set up right from the beginning.

The probability of God's existence can be quantified. The more information is required to make a first living cell, the more improbable it is that such a message came by by unguided means. Information simply is a quantitative measure of improbability. The higher the probability of a given event, the less information does it convey. Genetic molecules can only carry information based on unpredictable and aperiodic specified sequences that characterize instructional blueprints. Biological information must be understood as embracing the semiotic characteristic of information transmission and exchange analogous to human communication and language, based on syntax, pragmatics, and semantics. Statistical analysis however does not fully elucidate the problem. Mere improbability does not cover the real meaning or essence of information, measured in units of bits (or genes).

The price to be paid for this quantification is a loss of semantic content. In information theory, the value of information only reflects the statistical structure. But most statements in human communication are only understandable at a semantic level of analysis.

That becomes clear when one takes the semantic level of information into consideration, which introduces the concept of subjectiveness as a distinct category. Semiotics means signs, and those have meaning based on a convention agreed upon by someone entailed with intelligence. Only conscious agents can make sense of and interpret the meaning of a sign. And the information stored in cells is pregnant with meaning.

During the translation of genetic information into the amino acid sequence that forms functional polypeptide chains, that fold into proteins, through the ribosome machine, living systems are preprogrammed to give interpretations to incoming bits of information. A codon is assigned to amino acids utilizing the genetic code.  This state of affairs in biochemical systems is not a metaphorical description but translation is what is literally observed. The nucleic message is translated into the 'peptidic language'. That is analogous to a word in English being translated to a word in Chinese, where the meaning is equivalent.  If an intelligent designer is excluded to explain its origin, then natural, non-intelligent mechanisms become an external substitutive agent in the image of agency. I see this as a fallacy of misplaced reduction of what we only observe intelligence able to generate, to mere mechanistic natural causes.  

Analogy means 'similarity', or 'accordance'. An analogy is a relation between two descriptions of objects which allows inferences to be made about one on the basis of the other.  It is often of great value to construct and use analogies to clarify a state of affairs. It is valid to project the understanding of a concept, a causal order that we are familiar with, into the natural phenomena under study. An explanation can be understood as the description of natural phenomena, giving reference to an analogous system, like ordinary human language, mathematics, general physics etc. - that is already known, and so its causes. There is a signification-transfer involved between the different areas that is helpful to understand previously not known causal relationships.

Abduction - the process of inference to the best explanation captures this aspect of signification-transfer by analogy very well. Without our capacity to relate two bodies of knowledge abductively, realizing them as both falling under the same rules, we would have no science at all.  The argument by analogy is the fundamental technique in the process of understanding the world.

The Natural Theology of William Paley (1802) illustrates the concept of the book of nature as the sign of divinity in the Creation. The book of nature was often conceived as the visible sign of an otherwise invisible and transcendent God. It was readable by anyone, although the meaning of the book might be accessible only for the specially chosen.  The informational complexity of living systems points to the consciousness of the immanent larger mind of nature.

When "the hand of the creator" was replaced in the explanatory scheme by »natural selection«, it permitted incorporating most of the natural theology literature on living organisms almost unchanged into evolutionary biology. 
Natural selection became a modernized hand of God.

Biological systems start from the (digital) axioms and definitions and develop an analogic three-dimensional geometry: an instance of the morphology of life. Genotype is like a set of axioms, for instance Euclid's, and a phenotype is like a three-volume treatise on Euclidean geometry. 

The real-life of organisms in their ecological niche constitutes the more explorative phase of preprogrammed evolution, where selective and stochastic processes are in action. The termination of the life cycle occurs through sexual reproduction which corresponds to a 'back-translation' of the environmental experiences of the (analogic) population, to the digital level of epigenetic coding and the DNA inside the cohort of zygotes starting the next generation.

Deciphering of the DNA code has revealed our possession of a language much older than hieroglyphics, a language as old as life itself, a language that is the most living language at all - even if its letters are invisible and its words are buried in the cells of our bodies. When the structure of DNA was elucidated and the genetic code was broken, the concept of the organism as determined by a genetic program seemed to be an established biochemical fact, notwithstanding the enormous gap in knowledge about the epigenetic relationship between genotype and phenotype.

To state that an event is improbable, one first has to know that it might occur at all. Therefore the totally unforeseen - and thus the real new - cannot be accounted for through the statistical theory of probability. Semiotic functional information is not a tangible entity, and as such, it is beyond the reach of, and cannot be created by any undirected physical process. This is not an argument about probability. Conceptual semiotic information is simply beyond the sphere of influence of any undirected physical process. To suggest that a physical process can create semiotic code is like suggesting that a rainbow can write poetry... it is never going to happen!  Physics and chemistry alone do not possess the tools to create a concept. The only cause capable of creating conceptual semiotic information is a conscious intelligent mind. Life is no accident, the vast quantity of semiotic information in life provides powerful positive evidence that we have been designed.

To quote one scientist working at the cutting edge of our understanding of the programming information in biology, he described what he saw as an “alien technology written by an engineer a million times smarter than us”

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4The algorithmic origins of life Empty Re: The algorithmic origins of life Sun Dec 26, 2021 8:12 pm

Otangelo


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The algorithmic origins of life The_se10

1. The genetic code, and genetic information, are analogous to human language. Codons are words, the sequence of codons ( genes) are sentences. Both contain semantic meaning.
2. Codon words are assigned, and code for amino acids, and genes which are strings containing codified, complex specified information instruct the assembly of proteins.
3. Semantic meaning is non-material. Therefore, the origin of the genetic code, and genetic information, are non-material.
4. Instructional assembly information to make devices for specific purposes comes always from a mind. Therefore, genetic information comes from a mind.

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