All life possesses a non-material element: an extremely complex software code

Consider the structure of the deoxyribonucleic acid (DNA) molecule, the story of our understanding of its structure and function which is of itself a real scientific thriller. Only recently has man acquired an understanding of the advantages of having a generalized multipurpose machine, the computer, whose functional qualities are defined not by its physical characteristics, its hardware, but rather by the instructions that are applied to it in software code.

In its most straightforward functional context, the DNA molecule represents the purest, most compact and efficient structural embodiment imaginable of a chemically-implemented storage medium for software code. It reeks of anticipation, the creation of exquisitely complex order out of chaos.

DNA has a skeletal backbone structure consisting of alternate sugar and phosphate molecules interconnected to form a chain of arbitrary length. The size of this chain for most animals is quite huge. Functionally it is similar to the magnetic tape medium for the storage of computer software. Two such chains form a rail into which is embedded the actual software. Each side-by-side sugar-phosphate pair within this rail forms a nest for any one of four different hydrocarbon molecules from the following repertoire: adenine (labeled ‘A’), guanine (‘G’), cytosine (‘C’) and thymine (‘T’). An essential feature of these four chemicals is that they are always coded in pairs: A to T and C to G. On the surface, these pairs seem to represent just two possibilities, but in fact their physical reversal within the sugar-phosphate matrix adds another two possibilities. The four possibilities are: A-T, T-A, C-G, and G-C. An interesting feature of these pairs is that while A is of a different size than T, and C is of a different size than G, the two pairs are virtually identical in size, so that when one end of a pair nests on one sugar-phosphate chain and the other nests into the other sugar-phosphate chain, there is no distortion of the two-chain system due to size differences. Another interesting feature of the matrix is that the system has no preferential affinity for any one pair over another and no pair has an affinity for any other pair, rendering the system completely contingent, meaning that there is no bonding preference for any particular code pattern, a necessary feature of any true software encoding medium. Another key feature of the system is that it expresses chirality, which means that while there are two equally-probable directions in which the sugar and phosphate molecules bond together, the life-supporting nucleotides may only be of the right-handed form. This requirement alone radically decreases the probability, already vanishingly small, that the first DNA string was formed by chance.

The dual-nucleotide rail, together with the specific arrangement of embedded pairs within it, form what can only be characterized as a highly-organized structure of software code. But it does more than make a machine perform a function, because first it contains the instructions to build the machine itself.

Scientists haven’t yet decoded a single DNA string. What they have decoded is those portions of human DNA that are gene-specific, or the human genome, which represent but a tiny fraction of the entire string. Genes are sections of DNA code comprising software subroutines that specify and direct the manufacture of proteins. Even that portion of the overall decoding task is a major accomplishment, because the process by which a cell replicates a gene-specific portion in DNA into an RNA copy (RNA stands for ribonucleic acid), and then ‘reads’ the RNA code into the process that assembles the corresponding amino acids into another sequence representing a specific protein, is startlingly high-tech.

As added complicating factors, the amino acids, which also express chirality in their natural states, must all be of the left-handed variety, and only twenty out of a possible eighty amino acids are useful components of proteins.

Then there’s the ‘chicken-egg’ problem: proteins are manufactured from software instructions, but the software reader itself is a complex assembly of proteins. This situation implies that both the first software and the first hardware had to exist simultaneously. Given the enormous complexity of both, the odds against their simultaneous creation by chance alone are beyond astronomical.

These complicating factors simply add more baggage to the biggest problem of all: the sheer size of the code itself. Just the DNA within the cell of the simple bacterium of which the flagellum is a component contains far more than 100 thousand base pairs, or almost a thousand times the already-generous upper limit for chance. But that number represents just the minimum size of DNA in the first living cell, according to evolutionists.

In the early days of developing an understanding of the protein manufacture process, some of the scientists involved, being in an evolutionary frame of mind, considered the portions of DNA for which they could find no specific use to be “junk DNA”, DNA that represented earlier stages of evolution and was ignored for no longer being useful. Fortunately, other scientists, not so disposed to believe in evolution, discovered uses that included error-correcting codes like checksum values, and sequence-control commands like punctuation marks.

The discovery of what DNA is and does gave us an understanding of life that simply wasn’t accessible to Sir Charles Darwin or his contemporaries. Actually, this one insight has only been available to us for a few short decades, and it changes everything, particularly as we can only now view its implications in the context of some other very recent technological developments, including the structure of the computer and the development of information science, the understanding of which occurred simultaneously with our understanding of DNA.

The essence of life is information

William Dembski came to the conclusion several years ago that DNA represents pure information. Working within that paradigm, he successfully applied the principles of information science to life itself and from that synthesis developed the first principles of an exciting new mathematical discipline centered on the information-richness of life. In his book Intelligent Design, Dr. Dembski develops a theoretical model for naturalistic evolution in terms of the operation of chance on natural laws. From that he develops a well-defined, repeatable and probability-based means of scrutinizing a living system to distinguish a naturalistic process from the input of design. In the application of his procedure, the expressions dealing with probabilities are transformed into information-theoretical terminology, in effect equating odds to bits of information. Having performed that translation, Dr. Dembski offers a generous cutoff point of 500 bits of information, equivalent to a probability value of 10150, which represents a complexity so vast as to overwhelm the support of any time period proposed by the most ardent evolutionist. A system so complex as to represent over 500 bits of information, he claims, can exist only by the aid of design. Correspondingly, he inserts the value of 500 bits of information into his complexity criterion, thus reducing its evaluation to a straightforward and repeatable computation.

Dr. Dembski performs on biological systems the evaluation as directed by his process. If the system passes his pre-established hoops, then he concludes that a designer was involved in its existence. He has applied this procedure to several living systems, concluding that some of them exhibit irrefutable evidence of design.


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