Biomolecular systems like molecular motors or pumps, transcription and translation machinery, and other enzymatic reactions, can be described as Markov processes on a suitable network. We show quite generally that, in a steady state, the dispersion of observables, like the number of consumed or produced molecules or the number of steps of a motor, is constrained by the thermodynamic cost of generating it. An uncertainty ε requires at least a cost of 2k_B T/ε^2 independent of the time required to generate the output.
Life was long thought to obey its own set of rules. But as simple systems show signs of lifelike behavior, scientists are arguing about whether this apparent complexity is all a consequence of thermodynamics.
This is a nice little general interest article by Philip Ball that does a relatively good job of covering several of my favorite topics (information theory, biology, complexity) for the layperson. While it stays relatively basic, it links to a handful of really great references, many of which I’ve already read, though several appear to be new to me. 
While Ball has a broad area of interests and coverage in his work, he’s certainly one of the best journalists working in this subarea of interests today. I highly recommend his work to those who find this area interesting.
It is argued that if the non-unitary measurement transition, as codified by Von Neumann, is a real physical process, then the "probability assumption" needed to derive the Second Law of Thermodynamics naturally enters at that point. The existence of a real, indeterministic physical process underlying the measurement transition would therefore provide an ontological basis for Boltzmann's Stosszahlansatz and thereby explain the unidirectional increase of entropy against a backdrop of otherwise time-reversible laws. It is noted that the Transactional Interpretation (TI) of quantum mechanics provides such a physical account of the non-unitary measurement transition, and TI is brought to bear in finding a physically complete, non-ad hoc grounding for the Second Law.
Remarkable progress of quantum information theory (QIT) allowed to formulate mathematical theorems for conditions that data-transmitting or data-processing occurs with a non-negative entropy gain. However, relation of these results formulated in terms of entropy gain in quantum channels to temporal evolution of real physical systems is not thoroughly understood. Here we build on the mathematical formalism provided by QIT to formulate the quantum H-theorem in terms of physical observables. We discuss the manifestation of the second law of thermodynamics in quantum physics and uncover special situations where the second law can be violated. We further demonstrate that the typical evolution of energy-isolated quantum systems occurs with non-diminishing entropy. 
Jeremy England, a 31-year-old physicist at MIT, thinks he has found the underlying physics driving the origin and evolution of life.
- Jeremy L. England Lab
- Statistical physics of self-replication, Jeremy L. England; J. Chem. Phys. 139, 121923 (2013); doi: 10.1063/1.4818538
- Statistical Physics of Adaptation, Nikolai Perunov, Robert Marsland, and Jeremy England, arXiv, December 8, 2014
- Entropy production fluctuation theorem and the nonequilibrium work relation for free energy differences, Gavin E. Crooks, arXiv, February 1, 2008
- Life as a manifestation of the second law of thermodynamics, E.D. Schneider, J.J. Kay, doi:10.1016/0895-7177(94)90188-0, Mathematical and Computer Modelling, Volume 19, Issues 6–8, March–April 1994, Pages 25-48
Running a brain-twisting thought experiment for real shows that information is a physical thing – so can we now harness the most elusive entity in the cosmos?
This is a nice little overview article of some of the history of thermodynamics relating to information in physics and includes some recent physics advances as well. There are a few references to applications in biology at the micro level as well.
- Second Law of Thermodynamics with Discrete Quantum Feedback Control by Takahiro Sagawa and Masahito Ueda; Phys. Rev. Lett. 100, 080403 – Published 26 February 2008
- Work and information processing in a solvable model of Maxwell’s demon by Dibyendu Mandal and Christopher Jarzynski; PNAS vol. 109 no. 29, July 17, 2012
- Thermodynamic Costs of Information Processing in Sensory Adaptation by Pablo Sartori, Léo Granger, Chiu Fan Lee, and Jordan M. Horowitz; PLOS December 11, 2014 http://dx.doi.org.sci-hub.cc/10.1371/journal.pcbi.1003974
- Intermittent transcription dynamics for the rapid production of long transcripts of high fidelity by Depken M1, Parrondo JM, Grill SW; Cell Rep. 2013 Oct 31;5(2):521-30. doi: 10.1016/j.celrep.2013.09.007
- The stepping motor protein as a feedback control ratchet by Martin Bier; BioSystems 88 (2007) 301–307
AT LAST WE have it in English. Summa Technologiae, originally published in Polish in 1964, is the cornerstone of Stanislaw Lem’s oeuvre, his consummate work of speculative nonfiction. Trained in medicine and biology, Lem synthesizes the current science of the day in ways far ahead of most science fiction of the time.
His subjects, among others, include:
- Virtual reality
- Artificial intelligence
- Nanotechnology and biotechnology
- Evolutionary biology and evolutionary psychology
- Artificial life
- Information theory
- Entropy and thermodynamics
- Complexity theory, probability, and chaos
- Population and ecological catastrophe
- The “singularity” and “transhumanism”
I came across this book review quite serendipitously today via an Auerbach article in Slate, which I’ve bookmarked. I found a copy of the book and have added it to the top of my reading pile. As I’m currently reading an advance reader edition of Sean Carroll’s The Big Picture, I can only imagine how well the two may go together despite being written nearly 60 years apart.Syndicated copies to:
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)
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:
- 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:
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.
- References and Journal Articles
- Related Academic, Research Institutes, Societies, Groups, and Organizations
- Conferences, Workshops, and Symposia
- Bionet.Info-Theory (Google Group/Usenet Group)
- #ITBio on Twitter
Syndicated copies to:
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.
[My comments posted to the original Facebook post follow below.]
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:
- BIRS Workshop: Biological and Bio-Inspired Information Theory
- Entropy and Information in Biological Systems at NIMBios
- CECAM Workshop: Entropy in Biomolecular Systems
- ALife breakout session on Information Theoretic Incentives for Artificial Life (which will also spawn off a special issue of the journal Entropy):
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:
In recent years, ideas such as “life is information processing” or “information holds the key to understanding life” have become more common. However, how can information, or more formally Information Theory, increase our understanding of life, or life-like systems?
Information Theory not only has a profound mathematical basis, but also typically provides an intuitive understanding of processes, such as learning, behavior and evolution terms of information processing.
In this special issue, we are interested in both:
- the information-theoretic formalization and quantification of different aspects of life, such as driving forces of learning and behavior generation, information flows between neurons, swarm members and social agents, and information theoretic aspects of evolution and adaptation, and
- the simulation and creation of life-like systems with previously identified principles and incentives.
Topics with relation to artificial and natural systems:
- information theoretic intrinsic motivations
- information theoretic quantification of behavior
- information theoretic guidance of artificial evolution
- information theoretic guidance of self-organization
- information theoretic driving forces behind learning
- information theoretic driving forces behind behavior
- information theory in swarms
- information theory in social behavior
- information theory in evolution
- information theory in the brain
- information theory in system-environment distinction
- information theory in the perception action loop
- information theoretic definitions of life
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed Open Access monthly journal published by MDPI.
Deadline for manuscript submissions: 28 February 2015
Special Issue Editors
Dr. Christoph Salge
Adaptive Systems Research Group,University of Hertfordshire, College Lane, AL10 9AB Hatfield, UK
Phone: +44 1707 28 4490
Interests: Intrinsic Motivation (Empowerment); Self-Organization; Guided Self-Organization; Information-Theoretic Incentives for Social Interaction; Information-Theoretic Incentives for Swarms; Information Theory and Computer Game AI
Dr. Georg Martius
Cognition and Neurosciences, Max Planck Institute for Mathematics in the Sciences Inselstrasse 22, 04103 Leipzig, Germany
Phone: +49 341 9959 545
Interests: Autonomous Robots; Self-Organization; Guided Self-Organization; Information Theory; Dynamical Systems; Machine Learning; Neuroscience of Learning; Optimal Control
Dr. Keyan Ghazi-Zahedi
Information Theory of Cognitive Systems, Max Planck Institute for Mathematics in the Sciences Inselstrasse 22, 04103 Leipzig, Germany
Phone: +49 341 9959 535
Interests: Embodied Artificial Intelligence; Information Theory of the Sensorimotor Loop; Dynamical Systems; Cybernetics; Self-organisation; Synaptic plasticity; Evolutionary Robotics
Dr. Daniel Polani
Department of Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK
Interests: artificial intelligence; artificial life; information theory for intelligent information processing; sensor Evolution; collective and multiagent systems
On Friday, I had an excellent and stimulating conversation with Arieh Ben-Naim about his recent writing and work, and he mentioned in passing that he had been invited to a conference relating to entropy and biology in Vienna. A quick websearch found it quickly, and not having heard about it myself yet, I thought I’d pass it along to others who are regular readers and interested in the area.
The workshop on “Entropy in Biomolecular Systems” is being hosted by the Centre Européen de Calcul Atomique et Moléculaire (CECAM)
Location: DACAM, Max F. Perutz Laboratories, University of Vienna, Dr. Bohrgasse 9, A-1030, Vienna, Austria
Dates: May 14, 2014 to May 17, 2014
The workshop is being organized by:
- Richard Henchman (University of Manchester, United Kingdom)
- Bojan Zagrovic (University of Vienna, Austria)
- Michel Cuendet (Swiss Institute of Bioinformatics, Lausanne, Switzerland and Weill Cornell Medical College, New York, USA)
- Chris Oostenbrink (University of Natural Resources and Life Sciences, Austria)
It’s being supported by CECAM, the European Research Council, and the Royal Society of Chemistry’s Statistical Mechanics and Thermodynamics Group.
I’ll note that the registration deadline is on April 21 with a payment deadline of April 30, so check in quickly if you haven’t already.
The summary from the workshop website states:
This workshop brings together the world’s experts to address the challenges of determining the entropy of biomolecular systems, either by experiment or computer simulation. Entropy is one the main driving forces for any biological process such as binding, folding, partitioning and reacting. Our deficient understandng of entropy, however, means that such important processes remain controversial and only partially understood. Contributions of water, ions, cofactors, and biomolecular flexibility are actively examined but yet to be resolved. The state-of-the-art of each entropy method will be presented and explained, highlighting its capabilities and deficiencies. This will be followed by intensive discussion on the main areas that need improving, leading suitable actions and collaborations to address the main biological and industrial questions.
Further details on the workshop can be found on the CECAM website.
As always, details on other upcoming workshops and conferences relating to information theory and biology can be found on our ITBio Conferences/Workshops page.