Congratulations to Christoph Adami (@ChristophAdami) on release day for The Evolution of Biological Information: How Evolution Creates Complexity, from Viruses to Brains! I’m awaiting the post for my own hardcover copy. 

Bookmarked Tibor Gánti (1933- 2009): Towards the Principles of Life and Systems Chemistry (Journal of Theoretical Biology | sciencedirect.com)
Edited by Eörs Szathmáry
Volume 381, Pages 1-60 (21 September 2015)
Michael Marshall in He may have found the key to the origins of life. So why have so few heard of him? ()

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Bookmarked Vocabulary of Definitions of Life Suggests a Definition by Edward N. Trifonov (Journal of Biomolecular Structure and Dynamics Volume 29, 2011 - Issue 2)
Analysis of the vocabulary of 123 tabulated definitions of life reveals nine groups of defining terms (definientia) of which the groups (self-)reproduction and evolution (variation) appear as the minimal set for a concise and inclusive definition: Life is self-reproduction with variations.
https://doi.org/10.1080/073911011010524992

Michael Marshall in He may have found the key to the origins of life. So why have so few heard of him? ()

Bookmarked Cellular Homeostasis, Epigenesis and Replication in Randomly Aggregated Macromolecular Systems by Stuart A. Kauffman (Journal of Cybernetics Volume 1, 1971 - Issue 1)
Pages 71-96 | Published online: 15 Apr 2008
https://doi.org/10.1080/01969727108545830
Proto-organisms probably were randomly aggregated nets of chemical reactions. The hypothesis that contemporary organisms are also randomly constructed molecular automata is examined by modeling the gene as a binary (on-off) device and studying the behavior of large, randomly constructed nets of these binary “genes.” The results suggest that, if each “gene” is directly affected by two or three other “genes,” then such random nets: behave with great order and stability; undergo behavior cycles whose length predicts cell replication time as a function of the number of genes per cell; possess different modes of behavior whose number per net predicts roughly the number of cell types in an organism as a function of its number of genes; and under the stimulus of noise are capable of differentiating directly from any mode of behavior to at most a few other modes of behavior. Cellular differentiation is modeled as a Markov chain among the modes of behavior of a genetic net. The possibility of a general theory of metabolic behavior is suggested. Analytic approaches to the behavior of switching nets are discussed in Appendix 1, and some implications of the results for the origin of self replicating macromolecular systems is discussed in Appendix 6.

Michael Marshall in He may have found the key to the origins of life. So why have so few heard of him? ()

Bookmarked Budding and Division of Giant Vesicles Linked to Phospholipid Production by Juan M. Castro, Hironori Sugiyama, Taro Toyota (Scientific Reports volume 9, Article number: 165 (2019))
The self-reproduction of supramolecular assemblies based on the synthesis and self-assembly of building blocks is a critical step towards the construction of chemical systems with autonomous, adaptive, and propagation properties. In this report, we demonstrate that giant vesicles can grow and produce daughter vesicles by synthesizing and incorporating phospholipids in situ from ad-hoc precursors. Our model involves acyl chain elongation via copper(I)-catalyzed azide-alkyne [3 + 2] cycloaddition reaction and the ensuing production of synthetic phospholipids to induce budding and division. In addition, the growth and budding of giant vesicles were compatible with the encapsulation and transfer of macromolecules as large as lambda phage DNA to the buds. This chemical system provides a useful model towards the implementation of cell-like compartments capable of propagation and transport of biological materials.

Michael Marshall in He may have found the key to the origins of life. So why have so few heard of him? ()

Bookmarked Nonenzymatic Template-Directed RNA Synthesis Inside Model Protocells by Katarzyna Adamala (science.sciencemag.org)
The potential for self-replication makes RNA an attractive candidate as a primordial catalysis in the origin of life. Catalysis may have occurred in some kind of compartment, possibly a fatty acid vesicle. However, RNA catalysis generally requires high levels of magnesium, which are incompatible with fatty acid vesicle integrity. Adamala and Szostak (p. [1098][1]) screened magnesium chelators and found that several—including citrate, isocitrate, and oxalate—could maintain the membrane stability of fatty acid vesicles in the presence of Mg2+. Citrate also allowed Mg2+-dependent RNA synthesis within protocell-like vesicles, while at the same time protecting RNA from Mg2+-catalyzed degradation. Efforts to recreate a prebiotically plausible protocell, in which RNA replication occurs within a fatty acid vesicle, have been stalled by the destabilizing effect of Mg2+ on fatty acid membranes. Here we report that the presence of citrate protects fatty acid membranes from the disruptive effects of high Mg2+ ion concentrations while allowing RNA copying to proceed, while also protecting single-stranded RNA from Mg2+-catalyzed degradation. This combination of properties has allowed us to demonstrate the chemical copying of RNA templates inside fatty acid vesicles, which in turn allows for an increase in copying efficiency by bathing the vesicles in a continuously refreshed solution of activated nucleotides. [1]: /lookup/doi/10.1126/science.1241888

Michael Marshall in He may have found the key to the origins of life. So why have so few heard of him? ()

Read He may have found the key to the origins of life. So why have so few heard of him? by Michael MarshallMichael Marshall (Science)
Hungarian biologist Tibor Gánti is an obscure figure. Now, more than a decade after his death, his ideas about how life began are finally coming to fruition.
Good to see Tibor Gánti finally getting some credit. This is a great little article with a nice overview of the Origin of Life problem (and references). The author Michael Marshall has a new book out on the topic.

Peter Molnar in IndieWeb Chat ()

Read What Is an Individual? Biology Seeks Clues in Information Theory. (Quanta Magazine)
To recognize strange extraterrestrial life and solve biological mysteries on this planet, scientists are searching for an objective definition for life’s basic units.
I’ve been following a bit of David’s work, but obviously there’s some newer material I need to catch up on. I like the general philosophical thrust of their direction here. I can see some useful abstractions to higher math here, maybe an analogy to a “calculus of biology” which doesn’t look at single points, but rates of change of that point(s).
Read The Wuhan Virus: How to Stay Safe by Laurie Garrett (Foreign Policy)
As China’s epidemic continues to spread, things may seem scary. Here are 10 simple precautions that can protect you from contracting the coronavirus.

Some simple and easy to carry out precautions for the coming months.

On the Media Black Swans ()

👓 What can Schrödinger’s cat say about 3D printers on Mars? | Aeon | Aeon Essays

Read What can Schrödinger’s cat say about 3D printers on Mars? by Michael Lachmann and Sara Walker (Aeon | Aeon Essays)
A cat is alive, a sofa is not: that much we know. But a sofa is also part of life. Information theory tells us why
A nice little essay in my area, but I’m not sure there’s anything new in it for me. It is nice that they’re trying to break some of the problem down into smaller components before building it back up into something else. Reframing things can always be helpful. Here, in particular, they’re reframing the definitions of life and alive.

🔖 Origins Of Life | Complexity Explorer

Bookmarked Origins Of Life (complexityexplorer.org)

About the Course:

This course aims to push the field of Origins of Life research forward by bringing new and synthetic thinking to the question of how life emerged from an abiotic world.

This course begins by examining the chemical, geological, physical, and biological principles that give us insight into origins of life research. We look at the chemical and geological environment of early Earth from the perspective of likely environments for life to originate.

Taking a look at modern life we ask what it can tell us about the origin of life by winding the clock backwards. We explore what elements of modern life are absolutely essential for life, and ask what is arbitrary? We ponder how life arose from the huge chemical space and what this early 'living chemistry'may have looked like.

We examine phenomena, that may seem particularly life like, but are in fact likely to arise given physical dynamics alone. We analyze what physical concepts and laws bound the possibilities for life and its formation.

Insights gained from modern evolutionary theory will be applied to proto-life. Once life emerges, we consider how living systems impact the geosphere and evolve complexity. 

The study of Origins of Life is highly interdisciplinary - touching on concepts and principles from earth science, biology, chemistry, and physics.  With this we hope that the course can bring students interested in a broad range of fields to explore how life originated. 

The course will make use of basic algebra, chemistry, and biology but potentially difficult topics will be reviewed, and help is available in the course discussion forum and instructor email. There will be pointers to additional resources for those who want to dig deeper.

This course is Complexity Explorer's first Frontiers Course.  A Frontiers Course gives students a tour of an active interdisciplinary research area. The goals of a Frontiers Course are to share the excitement and uncertainty of a scientific area, inspire curiosity, and possibly draw new people into the research community who can help this research area take shape!

I’m totally in for this!

Hat tip for the reminder to:

Listened to Steven Johnson on the Importance of Play and the Decisions We Make by Alan Alda from Clear+Vivid with Alan Alda

How do we come up with ideas? How do we make decisions? And how can we do both better? Steven Johnson has explored this question and written a dozen books about it. In this playful, thoughtful episode, Steven has some fascinating stories, like how Darwin made the decision to get married — or how a defecating duck helped lead to the invention of the computer. Through their own stories, Steven and Alan Alda share their thoughts about the transformative nature of ideas and what sort of environments best give rise to creativity.

I love the idea of the slow hunch discussed here. It’s part of the reason I keep a commonplace book. Johnson also discusses his own personal commonplace book, though he doesn’t give it that particular name here.

The commercial about Alda Communication Training makes me wonder if they recommend scientists and communicators have their own websites? In particular, I’m even more curious because of Johnson’s mention of his commonplace book and how he uses it in this episode. I suspect that scientists having a variety of interconnecting commonplaces (via Webmention) using basic IndieWeb or A Domain of One’s Own principles could better create slow hunches, create more links, increase creativity and diversity, and foster greater innovation. I’ll have to follow up on this idea. While some may do something slightly like this within other parts of social media, I don’t get the impression that it’s as useful a tool in those places (isn’t as searchable or permanent feeling, and is likely rarely reviewed over). Being able to own your digital commonplace as a regular tool certainly has more value as Johnson describes. Functionality like On This Day dramatically increases its value.

But there’s another point that we should make more often, I think, which is that one of the most robust findings in the social sciences and psychology over the last 20 years is that diverse groups are just collectively smarter and more original in the way that they think in, in both their way of dreaming up new ideas, but also in making complicated decisions, that they avoid all the problems of group think and homogeneity that you get when you have a group of like minded people together who are just amplifying each other’s beliefs.—Steven Johnson [00:09:59]

Think about a big decision in your life. Think about the age span of the people you’re talking to about that choice. Are they all your peers within three or four years? Are you talking somebody who’s a generation older and a generation younger?—Steven Johnson [00:13:24]

I was talking to Ramzi Hajj yesterday about having mentors (with a clear emphasis on that mentor being specifically older) and this quote is the same sentiment, just with a slightly different emphasis.

One of the things that is most predictive of a species, including most famously, humans, of their capacity for innovation and problem solving as an adult is how much they play as a newborn or as a child.—Steven Johnson [00:28:10]

Play is important for problem solving.

I think you boil this all down into the idea that if you want to know what the next big thing is, look for where people are having fun.—Alan Alda [00:31:35]

This is interesting because I notice that one of the  binding (and even physically stated) principles of the IndieWeb is to have fun. Unconsciously, it’s one of the reasons I’ve always thought that what the group is doing is so important.

Ha! Alda has also been watching Shtisel recently [00:50:04].

📑 Solomon Golomb (1932–2016) | Stephen Wolfram Blog

Annotated Solomon Golomb (1932–2016) by Stephen Wolfram (blog.stephenwolfram.com)

As it happens, he’d already done some work on coding theory—in the area of biology. The digital nature of DNA had been discovered by Jim Watson and Francis Crick in 1953, but it wasn’t yet clear just how sequences of the four possible base pairs encoded the 20 amino acids. In 1956, Max Delbrück—Jim Watson’s former postdoc advisor at Caltech—asked around at JPL if anyone could figure it out. Sol and two colleagues analyzed an idea of Francis Crick’s and came up with “comma-free codes” in which overlapping triples of base pairs could encode amino acids. The analysis showed that exactly 20 amino acids could be encoded this way. It seemed like an amazing explanation of what was seen—but unfortunately it isn’t how biology actually works (biology uses a more straightforward encoding, where some of the 64 possible triples just don’t represent anything).  

I recall talking to Sol about this very thing when I sat in on a course he taught at USC on combinatorics. He gave me his paper on it and a few related issues as I was very interested at the time about the applications of information theory and biology.

I’m glad I managed to sit in on the class and still have the audio recordings and notes. While I can’t say that Newton taught me calculus, I can say I learned combinatorics from Golomb.

Bookmarked From bit to it: How a complex metabolic network transforms information into living matter by Andreas Wagner (BMC Systems Biology)

Background

Organisms live and die by the amount of information they acquire about their environment. The systems analysis of complex metabolic networks allows us to ask how such information translates into fitness. A metabolic network transforms nutrients into biomass. The better it uses information on available nutrient availability, the faster it will allow a cell to divide.

Results

I here use metabolic flux balance analysis to show that the accuracy I (in bits) with which a yeast cell can sense a limiting nutrient's availability relates logarithmically to fitness as indicated by biomass yield and cell division rate. For microbes like yeast, natural selection can resolve fitness differences of genetic variants smaller than 10-6, meaning that cells would need to estimate nutrient concentrations to very high accuracy (greater than 22 bits) to ensure optimal growth. I argue that such accuracies are not achievable in practice. Natural selection may thus face fundamental limitations in maximizing the information processing capacity of cells.

Conclusion

The analysis of metabolic networks opens a door to understanding cellular biology from a quantitative, information-theoretic perspective.

https://doi.org/10.1186/1752-0509-1-33

Received: 01 March 2007 Accepted: 30 July 2007 Published: 30 July 2007

Hat tip to Paul Davies in The Demon in the Machine