Intelligent design qualifies as a scientific theory
Hypothesis (Prediction): Natural structures will be found that contain many parts arranged in intricate patterns, metabolic pathways similar to electronic circuits, sophisticated language and translation systems, indicating high levels of Information, and interdependence, like hard/software. No information, nor codes or ciphers ( translators ) can exist and will be found without an initial mental source, since information is, by its nature, a mental and not a material quantity.
Observation: The genetic code system is a language , and the universal code is nearly optimal and maximally efficient ( only 1 in every million random alternative codes generated is more efficient than the genetic code ). Genomes use the genetic code to write two separate languages, beside a cipher, to translate codon triplets into a amino-acid "alphabet" constituent of 20 different left handed amino acids to make proteins. One code describes how proteins are made, and the other instructs the cell on how genes are controlled and when expressed. There are 13 characteristics of human language. DNA shares 10 of them ( all LEVELS of Information: Statistics, Syntax, Semantics, Pragmatics, Aprobatics are used ) This comparison between cell language and human language is not a loose analogy - it’s literal. Human language and cell language both employ multilayered symbols to produce a blueprint - required to describe a artifact, and in biology, a organism.
DNA sequences that code for proteins need to convey, in addition to the protein-coding information, several different signals at the same time. These “parallel codes” include binding sequences for regulatory and structural proteins, signals for splicing, and RNA secondary structure. The universal genetic code can efficiently carry arbitrary parallel codes much better than the vast majority of other possible genetic codes. This property is related to the identity of the stop codons. We find that the ability to support parallel codes is strongly tied to another useful property of the genetic code—minimization of the effects of frame-shift translation errors. Whereas many of the known regulatory codes reside in nontranslated regions of the genome, the present findings suggest that protein-coding regions can readily carry abundant additional information. The output are thousands of essential proteins and enzymes required for life; sophisticated molecular machinery is needed to replicate the code (for inheritance/perpetuation), transcribe it, translate it into protein with many intermediate steps requiring highly specific operations, and to repair it in the foreseen event that it is damaged (to preserve/protect it) or destroy it in the event that it suffers irreparable damage (to forestall cancer). Beside the standard genetic code, other 23 genetic codes are known, beside epigenetic codes, that is, the Splicing Code, the Metabolic Code, the Signal Transduction Codes, the Signal Integration Codes , the Histone Code, the Tubulin Code, the Sugar Code, and the Glycomic Code, all essential to define a organism and phenotype.
Experiment :
One language is written on top of the other, which is why the second language remained hidden for so long. Biologic systems and processes cannot be fully accounted for in terms of the principles and laws of physics and chemistry alone, but they require in addition the principles of semiotics—the science of symbols and signs, including linguistics. Summarizing the state of the art in the study of the code evolution, science cannot escape considerable skepticism. It seems that the two-pronged fundamental questions: “why is the genetic code the way it is and how did it come to be?”, that was asked over 50 years ago, at the dawn of molecular biology, might remain pertinent even in another 50 years, if methodological naturalism is adopted, and only natural explanations for its orgin are permitted. The consolation is that scientists cannot think of a more fundamental problem in biology. Despite extensive and, in many cases, elaborate attempts to model code optimization, ingenious theorizing along the lines of the coevolution theory, and considerable experimentation, very little definitive progress has been made.
Intelligent agents act frequently with an end goal in mind, constructing complex multipart-machines, that require a blueprint to build the object. Furthermore, Computers integrate software/hardware and store high levels of instructional complex coded information. In our experience, systems that either a) require or b) store large amounts of specified / instructed complex information such as codes and languages, and which are constructed in a interdependence of hard and software invariably originate from an intelligent source. No exception. There is a presence of an identical feature in both DNA and intelligently designed codes, languages, and artifacts. Because we know intelligent agents can (and do) produce complex and functionally specified sequences of symbols and arrangements of matter, intelligent agency qualifies as an adequate causal explanation for the origin of this effect. Since, in addition, materialistic theories have proven universally inadequate for explaining the origin of coded information and translation systems, intelligent causation stands as the only entity with the causal power known to produce this feature of living systems.
Falsification: Nobody has yet been able to demonstrate naturally emerging informational systems based on codes and ciphers, and instructional information stored within these codes to produce a defined complex specified outcome. Perry Marshall, author of the book Evolution 2.0, has yet to pay the prize to someone that will come up and will meet the challenge.
