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

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

Syndicated copies to:

## Network Science by Albert-László Barabási

Network Science by Albert-László Barabási(Cambridge University Press)

I ran across a link to this textbook by way of a standing Google alert, and was excited to check it out. I was immediately disappointed to think that I would have to wait another month and change for the physical textbook to be released, but made my pre-order directly. Then with a bit of digging around, I realized that individual chapters are available immediately to quench my thirst until the physical text is printed next month.

The textbook is available for purchase in September 2016 from Cambridge University Press. Pre-order now on Amazon.com.

Syndicated copies to:

## What is Information? by Christoph Adami

What is Information? [1601.06176] by Christoph Adami(arxiv.org)
Information is a precise concept that can be defined mathematically, but its relationship to what we call "knowledge" is not always made clear. Furthermore, the concepts "entropy" and "information", while deeply related, are distinct and must be used with care, something that is not always achieved in the literature. In this elementary introduction, the concepts of entropy and information are laid out one by one, explained intuitively, but defined rigorously. I argue that a proper understanding of information in terms of prediction is key to a number of disciplines beyond engineering, such as physics and biology.

A proper understanding of information in terms of prediction is key to a number of disciplines beyond engineering, such as physics and biology.

Comments: 19 pages, 2 figures. To appear in Philosophical Transaction of the Royal Society A
Subjects: Adaptation and Self-Organizing Systems (nlin.AO); Information Theory (cs.IT); Biological Physics (physics.bio-ph); Quantitative Methods (q-bio.QM)
Cite as:arXiv:1601.06176 [nlin.AO] (or arXiv:1601.06176v1 [nlin.AO] for this version)

[v1] Fri, 22 Jan 2016 21:35:44 GMT (151kb,D) [.pdf]

Source: Christoph Adami [1601.06176] What is Information? on arXiv

Syndicated copies to:

## The Information Universe Conference

"The Information Universe" Conference in The Netherlands in October hits several of the sweet spots for areas involving information theory, physics, the origin of life, complexity, computer science, and microbiology.

Yesterday, via a notification from Lanyard, I came across a notice for the upcoming conference “The Information Universe” which hits several of the sweet spots for areas involving information theory, physics, the origin of life, complexity, computer science, and microbiology. It is scheduled to occur from October 7-9, 2015 at the Infoversum Theater in Groningen, The Netherlands.

I’ll let their site speak for itself below, but they already have an interesting line up of speakers including:

### Keynote speakers

• Erik Verlinde, Professor Theoretical Physics, University of Amsterdam, Netherlands
• Alex Szalay, Alumni Centennial Professor of Astronomy, The Johns Hopkins University, USA
• Gerard ‘t Hooft, Professor Theoretical Physics, University of Utrecht, Netherlands
• Gregory Chaitin, Professor Mathematics and Computer Science, Federal University of Rio de Janeiro, Brasil
• Charley Lineweaver, Professor Astronomy and Astrophysics, Australian National University, Australia
• Lude Franke, Professor System Genetics, University Medical Center Groningen, Netherlands

### Conference synopsis from their homepage:

Additional details about the conference including the participants, program, venue, and registration can also be found at their website.

Syndicated copies to:

## NIMBioS Workshop: Information Theory and Entropy in Biological Systems

Web resources for participants in the NIMBioS Worshop on Information Theory and Entropy in Biological Systems.

Over the next few days, I’ll be maintaining a Storify story covering information related to and coming out of the Information Theory and Entropy Workshop being sponsored by NIMBios at the Unviersity of Tennessee, Knoxville.

For those in attendance or participating by watching the live streaming video (or even watching the video after-the-fact), please feel free to use the official hashtag #entropyWS, and I’ll do my best to include your tweets, posts, and material into the story stream for future reference.

For journal articles and papers mentioned in/at the workshop, I encourage everyone to join the Mendeley.com group ITBio: Information Theory, Microbiology, Evolution, and Complexity and add them to the group’s list of papers. Think of it as a collaborative online journal club of sorts.

Those participating in the workshop are also encouraged to take a look at a growing collection of researchers and materials I maintain here. If you have materials or resources you’d like to contribute to the list, please send me an email or include them via the suggestions/submission form or include them in the comments section below.

## Resources for Information Theory and Biology

Syndicated copies to:

## BIRS Workshop on Biological and Bio-Inspired Information Theory | Storify Stream

Over the span of the coming week, I'll be updating (and archiving) the stream of information coming out of the BIRS Workshop on Biological and Bio-Inspired Information Theory.

Over the span of the coming week, I’ll be updating (and archiving) the stream of information coming out of the BIRS Workshop on Biological and Bio-Inspired Information Theory.

## Information Theory is the New Central Discipline

Information Theory is the new central discipline. by Nassim Nicholas Taleb(facebook.com)

I’m coming to this post a bit late as I’m playing a bit of catch up, but agree with it wholeheartedly.

In particular, applications to molecular biology and medicine are really beginning to come to a heavy boil in just the past five years. This particular year is the progenitor of what appears to be the biggest renaissance for the application of information theory to the area of biology since Hubert Yockey, Henry Quastler, and Robert L. Platzman’s “Symposium on Information Theory in Biology at Gatlinburg, Tennessee” in 1956.

Upcoming/recent conferences/workshops on information theory in biology include:

At the beginning of September, Christoph Adami posted an awesome and very sound paper on arXiv entitled “Information-theoretic considerations concerning the origin of life”  which truly portends to turn the science of the origin of life on its head.

I’ll note in passing, for those interested, that Claude Shannon’s infamous master’s thesis at MIT (in which he applied Boolean Algebra to electric circuits allowing the digital revolution to occur) and his subsequent “The Theory of Mathematical Communication” were so revolutionary, nearly everyone forgets his MIT Ph.D. Thesis “An Algebra for Theoretical Genetics” which presaged the areas of cybernetics and the current applications of information theory to microbiology and are probably as seminal as Sir R.A Fisher’s applications of statistics to science in general and biology in particular.

For those commenting on the post who were interested in a layman’s introduction to information theory, I recommend John Robinson Pierce’s An Introduction to Information Theory: Symbols, Signals and Noise (Dover has a very inexpensive edition.) After this, one should take a look at Claude Shannon’s original paper. (The MIT Press printing includes some excellent overview by Warren Weaver along with the paper itself.) The mathematics in the paper really aren’t too technical, and most of it should be comprehensible by most advanced high school students.

For those that don’t understand the concept of entropy, I HIGHLY recommend Arieh Ben-Naim’s book Entropy Demystified The Second Law Reduced to Plain Common Sense with Seven Simulated Games. He really does tear the concept down into its most basic form in a way I haven’t seen others come remotely close to and which even my mother can comprehend (with no mathematics at all).  (I recommend this presentation to even those with Ph.D.’s in physics because it is so truly fundamental.)

For the more advanced mathematicians, physicists, and engineers Arieh Ben-Naim does a truly spectacular job of extending ET Jaynes’ work on information theory and statistical mechanics and comes up with a more coherent mathematical theory to conjoin the entropy of physics/statistical mechanics with that of Shannon’s information theory in A Farewell to Entropy: Statistical Thermodynamics Based on Information.

For the advanced readers/researchers interested in more at the intersection of information theory and biology, I’ll also mention that I maintain a list of references, books, and journal articles in a Mendeley group entitled “ITBio: Information Theory, Microbiology, Evolution, and Complexity.”

Syndicated copies to:

## How to Sidestep Mathematical Equations in Popular Science Books

In the publishing industry there is a general rule-of-thumb that every mathematical equation included in a book will cut the audience of science books written for a popular audience in half – presumably in a geometric progression. This typically means that including even a handful of equations will give you an effective readership of zero – something no author and certainly no editor or publisher wants.

I suspect that there is a corollary to this that every picture included in the text will help to increase your readership, though possibly not by as proportionally a large amount.

In any case, while reading Melanie Mitchell’s text Complexity: A Guided Tour [Cambridge University Press, 2009] this weekend, I noticed that, in what appears to be a concerted effort to include an equation without technically writing it into the text and to simultaneously increase readership by including a picture, she cleverly used a picture of Boltzmann’s tombstone in Vienna! Most fans of thermodynamics will immediately recognize Boltzmann’s equation for entropy, $S = k log W$, which appears engraved on the tombstone over his bust.

I hope that future mathematicians, scientists, and engineers will keep this in mind and have their tombstones engraved with key formulae to assist future authors in doing the same – hopefully this will help to increase the amount of mathematics that is deemed “acceptable” by the general public.

## Book Review: John Avery’s “Information Theory and Evolution”

Information Theory and Evolution
John Avery
Non-fiction, Popular Science
World Scientific
January 1, 2003
paperback
217

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.