The next [major] thrust [in biology], the one that may bring us closer to the Archimedian ideal of science, we may expect to come from information theory.
Though there is a paucity of equations, particularly on the information theoretic side, Loewenstein does a fantastic job of discussing the theory and philosophy of what is going on in the overlapping fields of information theory and microbiology. (I will note that it is commonly held wisdom within publishing, particularly for books for the broader public, that the number of equations in a text is inversely proportional to the number of sales and I’m sure this is the reason for the lack of mathematical substantiation which he could easily have supplied.)
This is a much more specific and therefore much better – in my mind – book than John Avery’s Information Theory and Evolution which covers some similar ground. Loewenstein has a much better and more specific grasp of the material in my opinion. Those who feel overwhelmed by Loewenstein may prefer to take a step back to Avery’s more facile presentation.
Loewenstein has a deft ability to describe what is going on and give both an up-close view with many examples as well as a spectacular view of the broader picture – something which is often missing in general science books of this sort. Readers with no mathematical or microbiology background can benefit from it as much as those with more experience.
One thing which sets it apart from much of its competition, even in the broader general science area of non-fiction, is that the author has a quirky but adept ability to add some flowery language and analogy to clarify his points. Though many will find this off-putting, it really does add some additional flavor to what might be dry and dull explication to many. His range of background knowledge, philosophy and vocabulary are second only (and possibly even on par or exceeding in some cases) that of Simon Winchester.
I’d highly recommend this book to people prior to their academic studies of biochemistry or molecular cell biology or to budding biomedical engineers prior to their junior year of study. I truly wish I had read this in 1994 myself, but alas it didn’t exist until a few years after. I lament that I hadn’t picked it up and been able to read it thoroughly until now.
For my part, his drastically differing viewpoint of the way in which biology should be viewed moving forward, is spot on. I am firmly a member of this new “school”. His final chapter on this concept is truly illuminating from a philosophical and theoretical view and I encourage people to read it first instead of last.
I’ll also note briefly that I’ve seen some reviews of this book which make mention of creationism or intelligent design and whether or not proponents of those philosophies feel that Loewenstein’s work here supports them or not, particularly since Loewenstein appeared on a panel with Dembski once. I will state for those who take a purely scientific viewpoint of things, that this book is written in full support of evolution and microbiology and doesn’t use the concept of “information” to muddy the waters the way many ID arguments are typically made.
How do we search for alien life if it's nothing like the life that we know? Christoph Adami shows how he uses his research into artificial life -- self-replicating computer programs -- to find a signature, a "biomarker," that is free of our preconceptions of what life is.
This highly interdisciplinary book discusses the phenomenon of life, including its origin and evolution (and also human cultural evolution), against the background of thermodynamics, statistical mechanics, and information theory. Among the central themes is the seeming contradiction between the second law of thermodynamics and the high degree of order and complexity produced by living systems. This paradox has its resolution in the information content of the Gibbs free energy that enters the biosphere from outside sources, as the author shows. The role of information in human cultural evolution is another focus of the book. One of the final chapters discusses the merging of information technology and biotechnology into a new discipline — bio-information technology.
This is a fantastic book which, for the majority of people, I’d give a five star review. For my own purposes, however, I was expecting far more on the theoretical side of information theory and statistical mechanics as applied to microbiology that it didn’t live up to, so I’m giving it three stars from a purely personal perspective.
I do wish that someone had placed it in my hands and forced me to read it when I was a freshman in college entering the study of biomedical and electrical engineering. It is far more an impressive book at this level and for those in the general public who are interested in the general history of science and philosophy of the topics. The general reader may be somewhat scared by a small amount of mathematics in chapter 4, but there is really no loss of continuity by skimming through most of it. For those looking for a bit more rigor, Avery provides some additional details in appendix A, but for the specialist, the presentation is heavily lacking.
The book opens with a facile but acceptable overview of the history of the development for the theory of evolution whereas most other texts would simply begin with Darwin’s work and completely skip the important philosophical and scientific contributions of Aristotle, Averroes, Condorcet, Linnaeus, Erasmus Darwin, Lamarck, or the debates between Cuvier and St. Hilaire.
For me, the meat of the book was chapters 3-5 and appendix A which collectively covered molecular biology, evolution, statistical mechanics, and a bit of information theory, albeit from a very big picture point of view. Unfortunately the rigor of the presentation and the underlying mathematics were skimmed over all too quickly to accomplish what I had hoped to gain from the text. On the other hand, the individual sections of “suggestions for further reading” throughout the book seem well researched and offer an acceptable launching pad for delving into topics in places where they may be covered more thoroughly.
The final several chapters become a bit more of an overview of philosophy surrounding cultural evolution and information technology which are much better covered and discussed in James Gleick’s recent book The Information.
Overall, Avery has a well laid out outline of the broad array of subjects and covers it all fairly well in an easy to read and engaging style.
A portion of Charles Darwin’s vast scientific library—including handwritten notes that the 19-century English naturalist scribbled in the margins of his books—has been digitized and is available online. Readers can now get a firsthand look into the mind of the man behind the theory of evolution.
The project to digitize Darwin’s extensive library, which includes 1,480 scientific books, was a joint effort with the University of Cambridge, the Darwin Manuscripts Project at the American Museum of Natural History, the Natural History Museum in Britain, and the Biodiversity Heritage Library.
The digital library, which includes 330 of the most heavily annotated books in the collection, is fully indexed—allowing readers to search through transcriptions of the naturalist’s handwritten notes that were compiled by the Darwin scholars Mario A. Di Gregorio and Nick Gill in 1990.
We describe the evolution of macromolecules as an information transmission process and apply tools from Shannon information theory to it. This allows us to isolate three independent, competing selective pressures that we term compression, transmission, and neutrality selection. The first two affect genome length: the pressure to conserve resources by compressing the code, and the pressure to acquire additional information that improves the channel, increasing the rate of information transmission into each offspring. Noisy transmission channels (replication with mutations) gives rise to a third pressure that acts on the actual encoding of information; it maximizes the fraction of mutations that are neutral with respect to the phenotype. This neutrality selection has important implications for the evolution of evolvability. We demonstrate each selective pressure in experiments with digital organisms.
To be published in J. theor. Biology 222 (2003) 477-483
DOI: 10.1016/S0022-5193(03)00062-6
This is the third in a series of three papers devoted to energy flow and entropy changes in chemical and biological processes, and their relations to the thermodynamics of computation. The previous two papers have developed reversible chemical transformations as idealizations for studying physiology and natural selection, and derived bounds from the second law of thermodynamics, between information gain in an ensemble and the chemical work required to produce it. This paper concerns the explicit mapping of chemistry to computation, and particularly the Landauer decomposition of irreversible computations, in which reversible logical operations generating no heat are separated from heat-generating erasure steps which are logically irreversible but thermodynamically reversible. The Landauer arrangement of computation is shown to produce the same entropy-flow diagram as that of the chemical Carnot cycles used in the second paper of the series to idealize physiological cycles. The specific application of computation to data compression and error-correcting encoding also makes possible a Landauer analysis of the somewhat different problem of optimal molecular recognition, which has been considered as an information theory problem. It is shown here that bounds on maximum sequence discrimination from the enthalpy of complex formation, although derived from the same logical model as the Shannon theorem for channel capacity, arise from exactly the opposite model for erasure.
https://doi.org/10.1016/j.jtbi.2008.02.013
This is the second in a series of three papers devoted to energy flow and entropy changes in chemical and biological processes, and to their relations to the thermodynamics of computation. In the first paper of the series, it was shown that a general-form dimensional argument from the second law of thermodynamics captures a number of scaling relations governing growth and development across many domains of life. It was also argued that models of physiology based on reversible transformations provide sensible approximations within which the second-law scaling is realized. This paper provides a formal basis for decomposing general cyclic, fixed-temperature chemical reactions, in terms of the chemical equivalent of Carnot's cycle for heat engines. It is shown that the second law relates the minimal chemical work required to perform a cycle to the Kullback–Leibler divergence produced in its chemical output ensemble from that of a Gibbs equilibrium. Reversible models of physiology are used to create reversible models of natural selection, which relate metabolic energy requirements to information gain under optimal conditions. When dissipation is added to models of selection, the second-law constraint is generalized to a relation between metabolic work and the combined energies of growth and maintenance.
https://doi.org/10.1016/j.jtbi.2008.02.008
This is the first of three papers analyzing the representation of information in the biosphere, and the energetic constraints limiting the imposition or maintenance of that information. Biological information is inherently a chemical property, but is equally an aspect of control flow and a result of processes equivalent to computation. The current paper develops the constraints on a theory of biological information capable of incorporating these three characterizations and their quantitative consequences. The paper illustrates the need for a theory linking energy and information by considering the problem of existence and reslience of the biosphere, and presents empirical evidence from growth and development at the organismal level suggesting that the theory developed will capture relevant constraints on real systems. The main result of the paper is that the limits on the minimal energetic cost of information flow will be tractable and universal whereas the assembly of more literal process models into a system-level description often is not. The second paper in the series then goes on to construct reversible models of energy and information flow in chemistry which achieve the idealized limits, and the third paper relates these to fundamental operations of computation.
https://doi.org/10.1016/j.jtbi.2008.02.010
No one can escape a sense of wonder when looking at an organism from within. From the humblest amoeba to man, from the smallest cell organelle to the amazing human brain, life presents us with example after example of highly ordered cellular matter, precisely organized and shaped to perform coordinated functions. But where does this order spring from? How does a living organism manage to do what nonliving things cannot do--bring forth and maintain all that order against the unrelenting, disordering pressures of the universe? In The Touchstone of Life, world-renowned biophysicist Werner Loewenstein seeks answers to these ancient riddles by applying information theory to recent discoveries in molecular biology. Taking us into a fascinating microscopic world, he lays bare an all-pervading communication network inside and between our cells--a web of extraordinary beauty, where molecular information flows in gracefully interlaced circles. Loewenstein then takes us on an exhilarating journey along that web and we meet its leading actors, the macromolecules, and see how they extract order out of the erratic quantum world; and through the powerful lens of information theory, we are let in on their trick, the most dazzling of magician's acts, whereby they steal form out of formlessness. The Touchstone of Life flashes with fresh insights into the mystery of life. Boldly straddling the line between biology and physics, the book offers a breathtaking view of that hidden world where molecular information turns the wheels of life. Loewenstein makes these complex scientific subjects lucid and fascinating, as he sheds light on the most fundamental aspects of our existence.
This highly interdisciplinary book discusses the phenomenon of life, including its origin and evolution (and also human cultural evolution), against the background of thermodynamics, statistical mechanics, and information theory. Among the central themes is the seeming contradiction between the second law of thermodynamics and the high degree of order and complexity produced by living systems. This paradox has its resolution in the information content of the Gibbs free energy that enters the biosphere from outside sources, as the author shows. The role of information in human cultural evolution is another focus of the book. One of the final chapters discusses the merging of information technology and biotechnology into a new discipline — bio-information technology.
Information Theory, Evolution and the Origin of Life presents a timely introduction to the use of information theory and coding theory in molecular biology. The genetical information system, because it is linear and digital, resembles the algorithmic language of computers. George Gamow pointed out that the application of Shannon's information theory breaks genetics and molecular biology out of the descriptive mode into the quantitative mode and Dr Yockey develops this theme, discussing how information theory and coding theory can be applied to molecular biology. He discusses how these tools for measuring the information in the sequences of the genome and the proteome are essential for our complete understanding of the nature and origin of life. The author writes for the computer competent reader who is interested in evolution and the origins of life.
The transmission of genomic information from coding sequence to protein structure during protein synthesis is subject to stochastic errors. To analyze transmission limits in the presence of spurious errors, Shannon's noisy channel theorem is applied to a communication channel between amino acid sequences and their structures established from a large-scale statistical analysis of protein atomic coordinates. While Shannon's theorem confirms that in close to native conformations information is transmitted with limited error probability, additional random errors in sequence (amino acid substitutions) and in structure (structural defects) trigger a decrease in communication capacity toward a Shannon limit at 0.010 bits per amino acid symbol at which communication breaks down. In several controls, simulated error rates above a critical threshold and models of unfolded structures always produce capacities below this limiting value. Thus an essential biological system can be realistically modeled as a digital communication channel that is (a) sensitive to random errors and (b) restricted by a Shannon error limit. This forms a novel basis for predictions consistent with observed rates of defective ribosomal products during protein synthesis, and with the estimated excess of mutual information in protein contact potentials.
https://doi.org/10.1371/journal.pone.0003110
