🔖 Information theory, predictability, and the emergence of complex life

Bookmarked Information theory, predictability, and the emergence of complex life (arxiv.org)
Abstract: Despite the obvious advantage of simple life forms capable of fast replication, different levels of cognitive complexity have been achieved by living systems in terms of their potential to cope with environmental uncertainty. Against the inevitable cost associated to detecting environmental cues and responding to them in adaptive ways, we conjecture that the potential for predicting the environment can overcome the expenses associated to maintaining costly, complex structures. We present a minimal formal model grounded in information theory and selection, in which successive generations of agents are mapped into transmitters and receivers of a coded message. Our agents are guessing machines and their capacity to deal with environments of different complexity defines the conditions to sustain more complex agents.

🔖 Foldscope – The Origami Paper Microscope | Kickstarter

Bookmarked Foldscope - The Origami Paper Microscope (Kickstarter)
See the invisible with a powerful yet affordable microscope that fits in your pocket. Curiosity, discovery, and science for everyone!
A microscope in every pocket is surely a great idea.

They also have a journal article on PLoS ONE[1]

References

[1]
J. Cybulski S., J. Clements, and M. Prakash, “Foldscope: Origami-Based Paper Microscope,” PLoS ONE, vol. 9, no. 6, Jun. 2014 [Online]. Available: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0098781 [Source]

🔖 100 years after Smoluchowski: stochastic processes in cell biology

Bookmarked 100 years after Smoluchowski: stochastic processes in cell biology (arxiv.org)
100 years after Smoluchowski introduces his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here the Smoluchowski's approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation.
65 pages, J. Phys A 2016 [1]

References

[1]
D. Holcman and Z. Schuss, “100 years after Smoluchowski: stochastic processes in cell biology,” arXiv, 26-Dec-2016. [Online]. Available: https://arxiv.org/abs/1612.08381. [Accessed: 03-Jan-2017]

Statistical Physics, Information Processing, and Biology Workshop at Santa Fe Institute

Bookmarked Information Processing and Biology by John Carlos Baez (Azimuth)
The Santa Fe Institute, in New Mexico, is a place for studying complex systems. I’ve never been there! Next week I’ll go there to give a colloquium on network theory, and also to participate in this workshop.
I just found out about this from John Carlos Baez and wish I could go! How have I not managed to have heard about it?

Stastical Physics, Information Processing, and Biology

Workshop

November 16, 2016 – November 18, 2016
9:00 AM
Noyce Conference Room

Abstract.
This workshop will address a fundamental question in theoretical biology: Does the relationship between statistical physics and the need of biological systems to process information underpin some of their deepest features? It recognizes that a core feature of biological systems is that they acquire, store and process information (i.e., perform computation). However to manipulate information in this way they require a steady flux of free energy from their environments. These two, inter-related attributes of biological systems are often taken for granted; they are not part of standard analyses of either the homeostasis or the evolution of biological systems. In this workshop we aim to fill in this major gap in our understanding of biological systems, by gaining deeper insight in the relation between the need for biological systems to process information and the free energy they need to pay for that processing.

The goal of this workshop is to address these issues by focusing on a set three specific question:

  1. How has the fraction of free energy flux on earth that is used by biological computation changed with time?;
  2. What is the free energy cost of biological computation / function?;
  3. What is the free energy cost of the evolution of biological computation / function.

In all of these cases we are interested in the fundamental limits that the laws of physics impose on various aspects of living systems as expressed by these three questions.

Purpose: Research Collaboration
SFI Host: David Krakauer, Michael Lachmann, Manfred Laubichler, Peter Stadler, and David Wolpert

Transplantation of spinal cord–derived neural stem cells for ALS

Favorited Transplantation of spinal cord–derived neural stem cells for ALS (neurology.org)
Analysis of phase 1 and 2 trials testing the safety of spinal cord transplantation of human stem cells in patients with amyotrophic lateral sclerosis (ALS) with escalating doses and expansion of the trial to multiple clinical centers.
I built the microinjectors used in these experiments for injecting stem cells into the first human patients.

CNN also has a general interest article talking about some of the results.

Links to some earlier articles:

Transplantation of spinal cord–derived neural stem cells for ALS

Analysis of phase 1 and 2 trials

Authors: Jonathan D. Glass, MD; Vicki S. Hertzberg, PhD; Nicholas M. Boulis, MD; Jonathan Riley, MD; Thais Federici, PhD; Meraida Polak, RN; Jane Bordeau, RN; Christina Fournier, MD; Karl Johe, PhD; Tom Hazel, PhD; Merit Cudkowicz, MD; Nazem Atassi, MD; Lawrence F. Borges, MD; Seward B. Rutkove, MD; Jayna Duell, RN; Parag G. Patil, MD; Stephen A. Goutman, MD; Eva L. Feldman, MD, PhD

ABSTRACT

Objective: To test the safety of spinal cord transplantation of human stem cells in patients with amyotrophic lateral sclerosis (ALS) with escalating doses and expansion of the trial to multiple clinical centers.

Methods: This open-label trial included 15 participants at 3 academic centers divided into 5 treatment groups receiving increasing doses of stem cells by increasing numbers of cells/injection and increasing numbers of injections. All participants received bilateral injections into the cervical spinal cord (C3-C5). The final group received injections into both the lumbar (L2-L4) and cervical cord through 2 separate surgical procedures. Participants were assessed for adverse events and progression of disease, as measured by the ALS Functional Rating Scale–Revised, forced vital capacity, and quantitative measures of strength. Statistical analysis focused on the slopes of decline of these phase 2 trial participants alone or in combination with the phase 1 participants (previously reported), comparing these groups to 3 separate historical control groups.

Results: Adverse events were mostly related to transient pain associated with surgery and to side effects of immunosuppressant medications. There was one incident of acute postoperative deterioration in neurologic function and another incident of a central pain syndrome. We could not discern differences in surgical outcomes between surgeons. Comparisons of the slopes of decline with the 3 separate historical control groups showed no differences in mean rates of progression.

Conclusions: Intraspinal transplantation of human spinal cord–derived neural stem cells can be safely accomplished at high doses, including successive lumbar and cervical procedures. The procedure can be expanded safely to multiple surgical centers.

Classification of evidence: This study provides Class IV evidence that for patients with ALS, spinal cord transplantation of human stem cells can be safely accomplished and does not accelerate the progression of the disease. This study lacks the precision to exclude important benefit or safety issues.

Source: Transplantation of spinal cord–derived neural stem cells for ALS

Workshop on Methods of Information Theory in Computational Neuroscience | CNS 2016

Bookmarked Workshop on Methods of Information Theory in Computational Neuroscience (CNS 2016) by Joseph T. Lizier (lizier.me)
Methods originally developed in Information Theory have found wide applicability in computational neuroscience. Beyond these original methods there is a need to develop novel tools and approaches that are driven by problems arising in neuroscience. A number of researchers in computational/systems neuroscience and in information/communication theory are investigating problems of information representation and processing. While the goals are often the same, these researchers bring different perspectives and points of view to a common set of neuroscience problems. Often they participate in different fora and their interaction is limited. The goal of the workshop is to bring some of these researchers together to discuss challenges posed by neuroscience and to exchange ideas and present their latest work. The workshop is targeted towards computational and systems neuroscientists with interest in methods of information theory as well as information/communication theorists with interest in neuroscience.

16w5113: Stochastic and Deterministic Models for Evolutionary Biology | Banff International Research Station

Bookmarked Stochastic and Deterministic Models for Evolutionary Biology (Banff International Research Station)
A BIRS / Casa Matemática Oaxaca Workshop arriving in Oaxaca, Mexico Sunday, July 31 and departing Friday August 5, 2016

Evolutionary biology is a rapidly changing field, confronted to many societal problems of increasing importance: impact of global changes, emerging epidemics, antibiotic resistant bacteria… As a consequence, a number of new problematics have appeared over the last decade, challenging the existing mathematical models. There exists thus a demand in the biology community for new mathematical models allowing a qualitative or quantitative description of complex evolution problems. In particular, in the societal problems mentioned above, evolution is often interacting with phenomena of a different nature: interaction with other organisms, spatial dynamics, age structure, invasion processes, time/space heterogeneous environment… The development of mathematical models able to deal with those complex interactions is an ambitious task. Evolutionary biology is interested in the evolution of species. This process is a combination of several phenomena, some occurring at the individual level (e.g. mutations), others at the level of the entire population (competition for resources), often consisting of a very large number of individuals. the presence of very different scales is indeed at the core of theoretical evolutionary biology, and at the origin of many of the difficulties that biologists are facing. The development of new mathematical models thus requires a joint work of three different communities of researchers: specialists of partial differential equations, specialists of probability theory, and theoretical biologists. The goal of this workshop is to gather researchers from each of these communities, currently working on close problematics. Those communities have usually few interactions, and this meeting would give them the opportunity to discuss and work around a few biological thematics that are especially challenging mathematically, and play a crucial role for biological applications.

The role of a spatial structure in models for evolution: The introduction of a spatial structure in evolutionary biology models is often challenging. It is however well known that local adaptation is frequent in nature: field data show that the phenotypes of a given species change considerably across its range. The spatial dynamics of a population can also have a deep impact on its evolution. Assessing e.g. the impact of global changes on species requires the development of robust mathematical models for spatially structured populations.

The first type of models used by theoretical biologists for this type of problems are IBM (Individual Based Models), which describe the evolution of a finite number of individuals, characterized by their position and a phenotype. The mathematical analysis of IBM in spatially homogeneous situations has provided several methods that have been successful in the theoretical biology community (see the theory of Adaptive Dynamics). On the contrary, very few results exist so far on the qualitative properties of such models for spatially structured populations.

The second class of mathematical approach for this type of problem is based on ”infinite dimensional” reaction-diffusion: the population is structured by a continuous phenotypic trait, that affects its ability to disperse (diffusion), or to reproduce (reaction). This type of model can be obtained as a large population limit of IBM. The main difficulty of these models (in the simpler case of asexual populations) is the term modeling the competition from resources, that appears as a non local competition term. This term prevents the use of classical reaction diffusion tools such as the comparison principle and sliding methods. Recently, promising progress has been made, based on tools from elliptic equations and/or Hamilton-Jacobi equations. The effects of small populations can however not be observed on such models. The extension of these models and methods to include these effects will be discussed during the workshop.

Eco-evolution models for sexual populations:An essential question already stated by Darwin and Fisher and which stays for the moment without answer (although it continues to intrigue the evolutionary biologists) is: ”Why does sexual reproduction maintain?” Indeed this reproduction way is very costly since it implies a large number of gametes, the mating and the choice of a compatible partner. During the meiosis phasis, half of the genetical information is lost. Moreover, the males have to be fed and during the sexual mating, individual are easy preys for predators. A partial answer is that recombination plays a main role by better eliminating the deleterious mutations and by increasing the diversity. Nevertheless, this theory is not completely satisfying and many researches are devoted to understanding evolution of sexual populations and comparison between asexual and sexual reproduction. Several models exist to model the influence of sexual reproduction on evolving species. The difficulty compared to asexual populations is that a detailed description of the genetic basis of phenotypes is required, and in particular include recombinations. For sexual populations, recombination plays a main role and it is essential to understand. All models require strong biological simplifications, the development of relevant mathematical methods for such mechanisms then requires a joint work of mathematicians and biologists. This workshop will be an opportunity to set up such collaborations.

The first type of model considers a small number of diploid loci (typically one locus and two alleles), while the rest of the genome is considered as fixed. One can then define the fitness of every combination of alleles. While allowing the modeling of specific sexual effects (such as dominant/recessive alleles), this approach neglects the rest of the genome (and it is known that phenotypes are typically influenced by a large number of loci). An opposite approach is to consider a large number of loci, each locus having a small and additive impact on the considered phenotype. This approach then neglects many microscopic phenomena (epistasis, dominant/recessive alleles…), but allows the derivation of a deterministic model, called the infinitesimal model, in the case of a large population. The construction of a good mathematical framework for intermediate situation would be an important step forward.

The evolution of recombination and sex is very sensitive to the interaction between several evolutionary forces (selection, migration, genetic drift…). Modeling these interactions is particularly challenging and our understanding of the recombination evolution is often limited by strong assumptions regarding demography, the relative strength of these different evolutionary forces, the lack of spatial structure… The development of a more general theoretical framework based on new mathematical developments would be particularly valuable.

Another problem, that has received little attention so far and is worth addressing, is the modeling of the genetic material exchanges in asexual population. This phenomena is frequent in micro-organisms : horizontal gene transfers in bacteria, reassortment or recombination in viruses. These phenomena share some features with sexual reproduction. It would be interesting to see if the effect of this phenomena can be seen as a perturbation of existing asexual models. This would in particular be interesting in spatially structured populations (e.g. viral epidemics), since the the mathematical analysis of spatially structured asexual populations is improving rapidly.

Modeling in evolutionary epidemiology: Mathematical epidemiology has been developing since more than a century ago. Yet, the integration of population genetics phenomena to epidemiology is relatively recent. Microbial pathogens (bacteria and viruses) are particularly interesting organisms because their short generation times and large mutation rates allow them to adapt relatively fast to changing environments. As a consequence, ecological (demography) and evolutionary (population genetics) processes often occur at the same pace. This raises many interesting problems.

A first challenge is the modeling of the spatial dynamics of an epidemics. The parasites can evolve during the epidemics of a new host population, either to adapt to a heterogeneous environment, or because it will itself modify the environment as it invades. The applications of such studies are numerous: antibiotic management, agriculture… An aspect of this problem for which our workshop can bring a significant contribution (thanks to the diversity of its participants) is the evolution of the pathogen diversity. During the large expansion produced by an epidemics, there is a loss of diversity in the invading parasites, since most pathogens originate from a few parents. The development of mathematical models for those phenomena is challenging: only a small number of pathogens are present ahead of the epidemic front, while the number of parasites rapidly become very large after the infection. The interaction between a stochastic micro scale and a deterministic macro scale is apparent here, and deserves a rigorous mathematical analysis.

Another interesting phenomena is the effect of a sudden change of the environment on a population of pathogens. Examples of such situations are for instance the antibiotic treatment of an infected patients, or the transmission of a parasite to a new host species (transmission of the avian influenza to human beings, for instance). Related experiments are relatively easy to perform, and called evolutionary rescue experiments. So far, this question has received limited attention from the mathematical community. The key is to estimate the probability that a mutant well adapted to the new environment existed in the original population, or will appear soon after the environmental change. Interactions between biologists specialists of those questions and mathematicians should lead to new mathematical problems.

Bits from Brains for Biologically Inspired Computing | Computational Intelligence

Bookmarked Bits from Brains for Biologically Inspired Computing (Frontiers in Robotics and AI | Computational Intelligence journal.frontiersin.org)
Inspiration for artificial biologically inspired computing is often drawn from neural systems. This article shows how to analyze neural systems using information theory with the aim of obtaining constraints that help to identify the algorithms run by neural systems and the information they represent. Algorithms and representations identified this way may then guide the design of biologically inspired computing systems. The material covered includes the necessary introduction to information theory and to the estimation of information-theoretic quantities from neural recordings. We then show how to analyze the information encoded in a system about its environment, and also discuss recent methodological developments on the question of how much information each agent carries about the environment either uniquely or redundantly or synergistically together with others. Last, we introduce the framework of local information dynamics, where information processing is partitioned into component processes of information storage, transfer, and modification – locally in space and time. We close by discussing example applications of these measures to neural data and other complex systems.

Nick Lane and Philip Ball Discuss Mitochondria, Sex, and How to Live Longer

Bookmarked Nick Lane and Philip Ball Discuss Mitochondria, Sex, and How to Live Longer by Philip Ball (Nautil.us)
In his 2010 book, Life Ascending: The Ten Great Inventions of Evolution, Nick Lane, a biochemist at University College London, explores with eloquence and clarity the big questions of life: how it began, why we age and die, and why we have sex. Lane been steadily constructing an alternative view of evolution to the one in which genes explain it all. He argues that some of the major events during evolutionary history, including the origin of life itself, are best understood by considering where the energy comes from and how it is used. Lane describes these ideas in his 2015 book, The Vital Question: Why Is Life the Way It Is?. Recently Bill Gates called it “an amazing inquiry into the origins of life,” adding, Lane “is one of those original thinkers who make you say: More people should know about this guy’s work.” Nautilus caught up with Lane in his laboratory in London and asked him about his ideas on aging, sex, and death.
Biochemist Nick Lane explains the elements of life, sex, and aging in an engaging popular science interview.

Read more

Books by Nick Lane

A new view of the tree of life

Bookmarked A new view of the tree of life (Nature Microbiology)
An update to the €˜tree of life has revealed a dominance of bacterial diversity in many ecosystems and extensive evolution in some branches of the tree. It also highlights how few organisms we have been able to cultivate for further investigation.

Abstract

The tree of life is one of the most important organizing principles in biology. Gene surveys suggest the existence of an enormous number of branches, but even an approximation of the full scale of the tree has remained elusive. Recent depictions of the tree of life have focused either on the nature of deep evolutionary relationships or on the known, well-classified diversity of life with an emphasis on eukaryotes. These approaches overlook the dramatic change in our understanding of life’s diversity resulting from genomic sampling of previously unexamined environments. New methods to generate genome sequences illuminate the identity of organisms and their metabolic capacities, placing them in community and ecosystem contexts. Here, we use new genomic data from over 1,000 uncultivated and little known organisms, together with published sequences, to infer a dramatically expanded version of the tree of life, with Bacteria, Archaea and Eukarya included. The depiction is both a global overview and a snapshot of the diversity within each major lineage. The results reveal the dominance of bacterial diversification and underline the importance of organisms lacking isolated representatives, with substantial evolution concentrated in a major radiation of such organisms. This tree highlights major lineages currently underrepresented in biogeochemical models and identifies radiations that are probably important for future evolutionary analyses.

Laura A. Hug, Brett J. Baker, Karthik Anantharaman, Christopher T. Brown, Alexander J. Probst, Cindy J. Castelle, Cristina N. Butterfield, Alex W. Hernsdorf, Yuki Amano, Kotaro Ise, Yohey Suzuki, Natasha Dudek, David A. Relman, Kari M. Finstad, Ronald Amundson, Brian C. Thomas & Jillian F. Banfield in Nature Microbiology, Article number: 16048 (2016) doi:10.1038/nmicrobiol.2016.48

 

A reformatted view of the tree in Fig. 1in which each major lineage represents the same amount of evolutionary distance.
A reformatted view of the tree in Fig. 1in which each major lineage represents the same amount of evolutionary distance.

Carl Zimmer also has a nice little write up of the paper in today’s New York Times:

Carl Zimmer
in Scientists Unveil New ‘Tree of Life’ from The New York Times 4/11/16

 

The Hidden Algorithms Underlying Life | Quanta Magazine

Bookmarked Searching for the Algorithms Underlying Life by John Pavlus (Quanta Magazine)
The biological world is computational at its core, argues computer scientist Leslie Valiant.

I did expect something more entertaining from Google when I searched for “what will happen if I squeeze a paper cup full of hot coffee?”

Forthcoming ITBio-related book from Sean Carroll: “The Big Picture: On the Origins of Life, Meaning, and the Universe Itself”

In catching up on blogs/reading from the holidays, I’ve noticed that physicist Sean Carroll has a forthcoming book entitled The Big Picture: On the Origins of Life, Meaning, and the Universe Itself (Dutton, May 10, 2016) that will be of interest to many of our readers. One can already pre-order the book via Amazon.

Prior to the holidays Sean wrote a blogpost that contains a full overview table of contents, which will give everyone a stronger idea of its contents. For convenience I’ll excerpt it below.

I’ll post a review as soon as a copy arrives, but it looks like a strong new entry in the category of popular science books on information theory, biology and complexity as well as potentially the areas of evolution, the origin of life, and physics in general.

As a side bonus, for those reading this today (1/15/16), I’ll note that Carroll’s 12 part lecture series from The Great Courses The Higgs Boson and Beyond (The Learning Company, February 2015) is 80% off.

The Big Picture

 

THE BIG PICTURE: ON THE ORIGINS OF LIFE, MEANING, AND THE UNIVERSE ITSELF

0. Prologue

* Part One: Cosmos

  • 1. The Fundamental Nature of Reality
  • 2. Poetic Naturalism
  • 3. The World Moves By Itself
  • 4. What Determines What Will Happen Next?
  • 5. Reasons Why
  • 6. Our Universe
  • 7. Time’s Arrow
  • 8. Memories and Causes

* Part Two: Understanding

  • 9. Learning About the World
  • 10. Updating Our Knowledge
  • 11. Is It Okay to Doubt Everything?
  • 12. Reality Emerges
  • 13. What Exists, and What Is Illusion?
  • 14. Planets of Belief
  • 15. Accepting Uncertainty
  • 16. What Can We Know About the Universe Without Looking at It?
  • 17. Who Am I?
  • 18. Abducting God

* Part Three: Essence

  • 19. How Much We Know
  • 20. The Quantum Realm
  • 21. Interpreting Quantum Mechanics
  • 22. The Core Theory
  • 23. The Stuff of Which We Are Made
  • 24. The Effective Theory of the Everyday World
  • 25. Why Does the Universe Exist?
  • 26. Body and Soul
  • 27. Death Is the End

* Part Four: Complexity

  • 28. The Universe in a Cup of Coffee
  • 29. Light and Life
  • 30. Funneling Energy
  • 31. Spontaneous Organization
  • 32. The Origin and Purpose of Life
  • 33. Evolution’s Bootstraps
  • 34. Searching Through the Landscape
  • 35. Emergent Purpose
  • 36. Are We the Point?

* Part Five: Thinking

  • 37. Crawling Into Consciousness
  • 38. The Babbling Brain
  • 39. What Thinks?
  • 40. The Hard Problem
  • 41. Zombies and Stories
  • 42. Are Photons Conscious?
  • 43. What Acts on What?
  • 44. Freedom to Choose

* Part Six: Caring

  • 45. Three Billion Heartbeats
  • 46. What Is and What Ought to Be
  • 47. Rules and Consequences
  • 48. Constructing Goodness
  • 49. Listening to the World
  • 50. Existential Therapy
  • Appendix: The Equation Underlying You and Me
  • Acknowledgments
  • Further Reading
  • References
  • Index

Source: Sean Carroll | The Big Picture: Table of Contents

Donald Forsdyke Indicates the Concept of Information in Biology Predates Claude Shannon

As it was published, I had read Kevin Hartnett’s article and interview with Christoph Adami The Information Theory of Life in Quanta Magazine. I recently revisited it and read through the commentary and stumbled upon an interesting quote relating to the history of information in biology:

Polymath Adami has ‘looked at so many fields of science’ and has correctly indicated the underlying importance of information theory, to which he has made important contributions. However, perhaps because the interview was concerned with the origin of life and was edited and condensed, many readers may get the impression that IT is only a few decades old. However, information ideas in biology can be traced back to at least 19th century sources. In the 1870s Ewald Hering in Prague and Samuel Butler in London laid the foundations. Butler’s work was later taken up by Richard Semon in Munich, whose writings inspired the young Erwin Schrodinger in the early decades of the 20th century. The emergence of his text – “What is Life” – from Dublin in the 1940s, inspired those who gave us DNA structure and the associated information concepts in “the classic period” of molecular biology. For more please see: Forsdyke, D. R. (2015) History of Psychiatry 26 (3), 270-287.

Donald Forsdyke, bioinformatician and theoretical biologist
in response to The Information Theory of Life in Quanta Magazine on

These two historical references predate Claude Shannon’s mathematical formalization of information in A Mathematical Theory of Communication (The Bell System Technical Journal, 1948) and even Erwin Schrödinger‘s lecture (1943) and subsequent book What is Life (1944).

For those interested in reading more on this historical tidbit, I’ve dug up a copy of the primary Forsdyke reference which first appeared on arXiv (prior to its ultimate publication in History of Psychiatry [.pdf]):

🔖 [1406.1391] ‘A Vehicle of Symbols and Nothing More.’ George Romanes, Theory of Mind, Information, and Samuel Butler by Donald R. Forsdyke  [1]
Submitted on 4 Jun 2014 (v1), last revised 13 Nov 2014 (this version, v2)

Abstract: Today’s ‘theory of mind’ (ToM) concept is rooted in the distinction of nineteenth century philosopher William Clifford between ‘objects’ that can be directly perceived, and ‘ejects,’ such as the mind of another person, which are inferred from one’s subjective knowledge of one’s own mind. A founder, with Charles Darwin, of the discipline of comparative psychology, George Romanes considered the minds of animals as ejects, an idea that could be generalized to ‘society as eject’ and, ultimately, ‘the world as an eject’ – mind in the universe. Yet, Romanes and Clifford only vaguely connected mind with the abstraction we call ‘information,’ which needs ‘a vehicle of symbols’ – a material transporting medium. However, Samuel Butler was able to address, in informational terms depleted of theological trappings, both organic evolution and mind in the universe. This view harmonizes with insights arising from modern DNA research, the relative immortality of ‘selfish’ genes, and some startling recent developments in brain research.

Comments: Accepted for publication in History of Psychiatry. 31 pages including 3 footnotes. Based on a lecture given at Santa Clara University, February 28th 2014, at a Bannan Institute Symposium on ‘Science and Seeking: Rethinking the God Question in the Lab, Cosmos, and Classroom.’

The original arXiv article also referenced two lectures which are appended below:

http://www.youtube.com/watch?v=a3yNbTUCPd4

[Original Draft of this was written on December 14, 2015.]

References

[1]
D. Forsdyke R., “‘A vehicle of symbols and nothing more’. George Romanes, theory of mind, information, and Samuel Butler,” History of Psychiatry, vol. 26, no. 3, Aug. 2015 [Online]. Available: http://journals.sagepub.com/doi/abs/10.1177/0957154X14562755

Quantum Biological Information Theory by Ivan B. Djordjevic | Springer

Bookmarked Quantum Biological Information Theory (Springer, 2015)
Springer recently announced the publication of the book Quantum Biological Information Theory by Ivan B. Djordjevic, in which I’m sure many readers here will have interest. I hope to have a review of it shortly after I’ve gotten a copy. Until then…

From the publisher’s website:

This book is a self-contained, tutorial-based introduction to quantum information theory and quantum biology. It serves as a single-source reference to the topic for researchers in bioengineering, communications engineering, electrical engineering, applied mathematics, biology, computer science, and physics. The book provides all the essential principles of the quantum biological information theory required to describe the quantum information transfer from DNA to proteins, the sources of genetic noise and genetic errors as well as their effects.

  • Integrates quantum information and quantum biology concepts;
  • Assumes only knowledge of basic concepts of vector algebra at undergraduate level;
  • Provides a thorough introduction to basic concepts of quantum information processing, quantum information theory, and quantum biology;
  • Includes in-depth discussion of the quantum biological channel modelling, quantum biological channel capacity calculation, quantum models of aging, quantum models of evolution, quantum models on tumor and cancer development, quantum modeling of bird navigation compass, quantum aspects of photosynthesis, quantum biological error correction.

Source: Quantum Biological Information Theory | Ivan B. Djordjevic | Springer

9783319228150I’ll note that it looks like it also assumes some reasonable facility with quantum mechanics in addition to the material listed above.

Springer also has a downloadable copy of the preface and a relatively extensive table of contents for those looking for a preview. Dr. Djordjevic has been added to the ever growing list of researchers doing work at the intersection of information theory and biology.