Striking architectural similarities between higher genomes and computer executable code


Josiah Seaman

Ph.D. student in Computational Biology at Colorado University, Denver, CO.


Josiah Seaman is a student of Bioinformatics. He has a bachelor's in Computer Science. He is currently working as a Ph.D student in Computational Biology at CU Denver. His specialties are data visualization and sequence analysis. He is the creator of Skittle Genome Visualizer ( which is being used to better understand chromosome structure and organization. The downloadable version is freely available (click here).



The human genome is highly repetitive at all scales. Repetitive sequences make up at least half the genome and have long been dismissed as non-functional DNA. They are explained in terms of replication errors or parasitic sequences while protein coding genes are assumed to be the primary functional unit of the cell. This paper focuses on tandem repeats but the same approach can be generalized to distributed repeats. A repeat consisting of perfect copies contains no information beyond its base sequence and the number of copies. However, using sequence visualization tools, what is actually observed in the human genome is that repetitive sequences contain many variations without exception. This opens up the possibility that these repeats can act as information carriers and be under selective pressure.


In the course of research, it was discovered that executable programs in computers use the same patterns of repetition in instructions that we observe in genome sequences. Despite the fact that they share none of the same physical mechanisms, genomes and computer programs have very similar structures. Once visualized, the similarities between executable code and the human genome are both striking and ubiquitous. Executable code makes extensive use of tandem repeats which show the same kinds of variation normally explained as insertions, deletions, and substitutions in biology. Furthermore, executable code shows the same large scale organization as chromosomes. Firstly, changing bias between the use of 1’s and 0’s creates the same distribution pattern as isochores alternating between A/T and G/C bias. Secondly, blocks of data are stored at the beginning or end of the file, while the primary instructions occupy the middle of the file. This creates the same organization pattern observed in human chromosomes where repetitive sequences are grouped near the telomeres and centromeres.


We propose that this similarity is caused by universal constraints in information encoding and execution. The genome is the executable program that encodes life. Given evidence that computers and genomes use many of the same patterns despite having very different origins, it is reasonable to ask what lessons learned in computer architecture can be applied to biology and vice versa.

Academy of Sciences USA. He is also the author of several books, including Charles Hodge’s Critique of Darwinism, Icons of Evolution and The Politically Incorrect Guide to Darwinism and Intelligent Design, and he is the co-author (with William Dembski) of The Design of Life. His most recent book, The Myth of Junk DNA, was published in 2011.



According to the most widely held modern version of Darwin’s theory, DNA mutations can supply raw materials for morphological evolution because they alter a genetic program that controls embryo development. Yet a genetic program is not sufficient for embryogenesis: Biological information outside of DNA is needed to specify the body plan of the embryo and much of its subsequent development. Some of that information is in cell membrane patterns, which contain a two-dimensional code mediated by proteins and carbohydrates. These molecules specify targets for morphogenetic determinants in the cytoplasm, generate endogenous electric fields that provide spatial coordinates for embryo development, regulate intracellular signaling, and participate in cell-cell interactions. Although the individual membrane molecules are at least partly specified by DNA sequences, their two-dimensional patterns are not. Furthermore, membrane patterns can be inherited independently of the DNA. I review some of the evidence for the membrane code and argue that it has important implications for modern evolutionary theory.

The membrane code: a carrier of essential biological information that is not specified by DNA and is inherited apart from it


Jonathan Wells

Discovery Institute, Seattle WA 98104.


Jonathan Wells holds an A.B. in Physical Sciences from the University of California at Berkeley. In 1985 he received a Ph.D. in Religious Studies from Yale University, with a dissertation on Charles Hodge and the nineteenth-century Darwinian controversies. In 1994 he received a second Ph.D. in Molecular and Cell Biology from the University of California at Berkeley, with a dissertation on frog embryology. From 1995 to 1998 he worked as a hospital laboratory supervisor and did postdoctoral research at Berkeley. He then moved with his family to Seattle, where he is now a Senior Research Fellow at the Discovery Institute. He has authored scientific articles in BioSystems, The Scientist, The American Biology Teacher and Rivista

di Biologia / Biology Review, and he has co-authored articles in Development and Proceedings of the

A new model of intracellular communication based on coherent, high-frequency vibrations in biomolecules


Laurieanne Dent

Department of Biology, Rockwell Hall, Grove City College, Grove City, PA 16127, USA.


Laurieanne Dent is a Visiting Professor of Biology at Pepperdine University where she teaches courses in physiology and zoology. In 2008, she completed doctoral studies at Cornell University in Neurobiology and Behavior with a minor in Genetics and Development. Her dissertation research was focused on brainstem neural circuits which process sub-millisecond communication stimuli from electric organ discharges of weakly-electric African mormyrid fish. As an undergraduate at Texas Christian University, she earned a B.S. in Biology and Secondary Teacher Certification in Composite Science, as well, in 1991. After teaching a diversity of science subjects and levels for several years as a secondary educator, she studied for a M.S. in Biology in physiological ecology at Sam Houston St. University in Huntsville, Texas.


Chemistry has been the ruling paradigm for understanding the communication network that integrates a living cell. However, biochemistry alone is insufficient to explain how widely separated biomolecules locate and move toward one another with precision and speed. We propose a new model wherein cytoplasmic motion is vibrationally directed due to a community of oscillating biomolecules.  DNA vibrations have been predicted in the 2-GHz range, thus we used high frequency laser-Doppler vibrometry to test the hypothesis that resonance-driven molecular motion would be detectable as picometer surface displacements in live onion epidermal cells and fish eggs but would be absent in dead cells. Although no surface vibrations were detected under these conditions, we discuss implications for the vibrational model of intracellular communication and suggest future experiments.

Accountant as a biologically-realistic computing tool for understanding the dynamics of mutation, selection, and random drift in natural populations.



In the light of the second law of thermodynamics, how can biological information be sustained, once it has come into existence?  It is well known that mutations, which are ubiquitous, systematically destroy biological information. Can natural selection halt the mutational degradation of genetic information?


Most deleterious mutations should have very slight effects on total fitness, and it has become clear that below a certain threshold, such low impact mutations fail to respond to natural selection. In this paper we use numerical simulation to examine this problem of “selection threshold.”  


Our investigations reveal that under circumstances which characterize most eukaryotic populations in nature, selection thresholds for deleterious mutations are surprisingly high. Our analysis of the selection threshold problem indicates that given even modest levels of biological noise, accumulation of low-impact mutations is far more serious than has been previously acknowledged. Indeed, we find that under most realistic circumstances, the large majority of harmful mutations are essentially unaffected by natural selection. This finding has major theoretical implications, and raises the question: “how can low-impact nucleotide positions, which constitute most of the information within a genome, be preserved through deep time?”

Can biological information be sustained by purifying natural selection?


Paul Gibson

Adjunct Associate Professor, Dept. of Plant, Soil, and Agricultural Systems, Southern Illinois University. Professor, Plant Genetics and Statistics, Cooperative Studies, Inc., Overland Park, KS.


Paul Gibson has had a career-long interest in theoretical quantitative genetics and its application to plant breeding for the improvement of food crops in hungry areas of the world. His Ph.D is in Plant Breeding and Cytogenetics from Iowa State University in 1981, with his dissertation research conducted at the International Crops Research Institute (ICRISAT) in India. After working as a maize breeder in Zambia, he conducted quantitative genetic and molecular research and taught at Southern Illinois University. Paul now serves as the primary instructor and mentor in a regional MSc and Ph.D program in Plant Breeding and Biotechnology at Makerere Univ. in Kampala, Uganda. He contributed to the development of Mendel’s

patents and the founder or board member of a number of biotechnology corporations. In 2008 he was elected a Fellow of the Royal Society of Canada. The author of over 180 scientific articles, he is the co-author of one book and the author of four others: Origins of Order: Self-Organization and Selection in Evolution (Oxford University Press 1993), At Home in the Universe: The Search for the Laws of Self-Organization and Complexity (Oxford University Press 1995), Investigations (Oxford University Press 2000) and Reinventing the Sacred (Basic Books 2008).



It is argued that no law entails the evolution of the biosphere. Biological evolution rests on both quantum random and classical non-random natural selection and whole-part interactions that render the sample space of adjacent biological possibilities unknowable. This would seem to create an insurmountable problem for intelligent design in biology. Nonetheless, the evolution of ensemblesof interacting systems can be modeled by statistical laws that have strong self-organizational properties. Some compelling examples modeling evolutionary self-organization in biology are presented and it is concluded that a new science of order and organization beyond entailing law is required.

Evolution Beyond Entailing Law: The Roles of Embodied Information and Self Organization


Stuart Kauffman

Professor of Biochemistry and Mathematics at the University of Vermont and Professsor of Computational Systems Biology at the Tampere University of Technnology in Finland.


Stuart A. Kauffman is currently Distinguished Professor of Biochemistry and Mathematics at the University of Vermont and Distinguished Professor of Computational Systems Biology at the Tampere University of Technology in Finland. He has also held professorships at the University of Chicago, the University of Pennsylvania, the Santa Fe Institute, the University of New Mexico, the Krasnow Institute at George Mason University, the M.D. Anderson Cancer Center, the University of Calgary, and Harvard Divinity School. A pioneer in the field of complexity theory, he is a biologist, trained as a medical doctor, who studies the origins of life and the origins of molecular organization. Kauffman is the holder of a dozen biotechnology


Towards a General Biology: Emergence of Life and Information from the Perspectives of Complex Systems Dynamics


Bruce H. Weber

Emeritus Professor of Biochemistry, California State University at Fullerton, and Robert H. Woodworth Chair in Science and Natural Philosophy Emeritus at Bennington College in Bennington, Vermont.


Bruce H. Weber is Emeritus Professor of Biochemistry, California State University at Fullerton, and Robert H. Woodworth Chair in Science and Natural Philosophy Emeritus at Bennington College in Bennington, Vermont. He is the author of numerous scientific articles and the co-author or co-editor of several books, including Evolution and Learning (MIT Press 2003), Darwinism Evolving: Systems Dynamics and the Genealogy of Natural Selection (MIT Press 1996), Evolution at a Crossroads: The New Biology and the New Philosophy of Science (MIT Press 1989), and Entropy, Information, and Evolution: New Perspectives on Physical and Biological Evolution (MIT Press 1988). His research interests are in macromolecular


evolution with special emphasis on the application of non-equilibrium thermodynamics to the problems of the emergence of life, and the history of biochemistry, especially the conceptual development of bioenergetics.



I argue that Darwinism is best described as a research tradition in which specific theories of how natural selection acts to produce common descent and evolutionary change are instantiated by specific dynamical assumptions. The current Darwinian research program is the genetical theory of natural selection, or the Modern Evolutionary Synthesis. Presently, however, there is ferment in the Darwinian Research Tradition as new knowledge from molecular and developmental biology, together with the deployment of complex systems dynamics, suggests that an expanded and extended evolutionary synthesis is possible, one that could be particularly robust in explaining the emergence of evolutionary novelties and even of life itself. Critics of Darwinism need to address such theoretical advances and not just respond to earlier versions of the research tradition.

An ode to the code: evidence for finetuning in the codon table


Jed C. Macosko

School of Mathematics, Wake Forest University.


Jed C. Macosko is an associate professor of biophysics at Wake Forest University. He graduated from MIT with the Merck award for outstanding scholarship and earned a Ph.D. in biophysical chemistry at the University of California, Berkeley in 1999 for his work on the molecular machinery of influenza, HIV and nerve cells. From 2000 to 2002 his research on molecular machines continued as an NIH postdoctoral fellow in the laboratory of Carlos J. Bustamante and then in 2003 and 2004 as an adjunct assistant professor working with David J. Keller at the University of New Mexico. Since 2004 the Macosko lab at Wake Forest has used in vivo and in vitro microscopy to study how molecular machines move cargo from one part of a cell to another. His team has developed a novel drug discovery platform based on combinatorial libraries of nucleic acid encoded chemicals. His studies on molecular machines and nucleic

acids have resulted in over 25 technical papers, book chapters and submitted patents, which have been cited nearly 1000 times and have provided further evidence for design in nature. He and his wife live in Winston-Salem with their five children.



The Standard Codon Table (SCT) records the correlation observed in nature between the complete set of 64 trinucleotides and 20 amino acids plus 3 nonsense codons. This table was called a “frozen accident” by Francis Crick, yet more recent evidence points to optimization that minimizes harmful effects of mutations and mistranslations while maximizing the encoding of multiple messages into a single sequence. For example, a 2000 article with the running title “The best of all possible codes?” concluded that “evidence is clear” for the optimized nature of the SCT, and a 2007 paper found that difficult-to-encode signals are minimized in the SCT. More recently, methionine’s role as the initiating amino acid has been found optimal in terms of minimal ribosome exiting barriers, and the 4-codons vs. <4-codons symmetry of the SCT has been explained in terms of minimizing mistranslation. I argue that the optimization of the SCT has its origin in external intelligence rather than in the adaptive selection of earlier codes.

Evolution: The Search for the Limits of Darwinism, which argue that living system at the molecular level are best explained as being the result of deliberate intelligent design. The books have been reviewed by the New York Times, Nature, Philosophy of Science, Christianity Today, and many other periodicals. He and his wife reside near Bethlehem, Pennsylvania, with their nine children.



Over the course of evolution organisms have adapted to their environments by mutating to gain new functions or to lose pre-existing ones. Because adaptation can occur by either of these modes, it is of basic interest to assess under what, if any, evolutionary circumstances one of them may predominate. Since mutation occurs at the molecular level, one must look there to discern if an adaptation involves gain- or loss-of-function. Here I present a simple, deterministic model for the occurrence and spread of adaptive gain-of-function versus loss-of-function mutations, and compare the results to laboratory evolution experiments and studies of evolution in nature. The results demonstrate that loss-of-function mutations generally have an intrinsic evolutionary rate advantage over gain-of-function mutations, but that the advantage depends radically on population size, ratio of selection coefficients of competing adaptive mutations, and ratio of the mutation rates to the adaptive states.

Getting there first: an evolutionary rate advantage for adaptive loss-off-function mutations

Michael J. Behe

Department of Biological Sciences, Lehigh University Bethlehem, PA 18015.


Michael J. Behe graduated from Drexel University in Philadelphia, with a Bachelor of Science degree in Chemistry. He did his graduate studies in biochemistry at the University of Pennsylvania and was awarded the Ph.D. for his dissertation research on sickle-cell disease. From 1978-1982 he did postdoctoral work on DNA structure at the National Institutes of Health. From 1982-85 he was Assistant Professor of Chemistry at Queens College in New York City, where he met his wife. In 1985 he moved to Lehigh University where he is currently Professor of Biochemistry. In his career he has authored over 40 technical papers and two books, Darwin’s Black Box: The Biochemical Challenge to Evolution: The Edge of