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.
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 intelligence.
- Life is therefore the direct product of a deliberate creative intellectual processes.
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 a 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 programing information in biology, he described what he saw as an “alien technology written by an engineer a million times smarter than us”
Information is not physical
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.
Three subsets of sequence complexity and their relevance to biopolymeric information
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.
The capabilities of chaos and complexity.
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 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
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
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
Last edited by Otangelo on Fri Nov 20, 2020 3:32 pm; edited 1 time in total