Investigating information storage and processing in biological systems
We work on novel ways to understand and control complex pattern formation. We use techniques of molecular genetics, biophysics, and computational modeling to address large-scale control of growth and form. We work in whole frogs and flatworms, and sometimes zebrafish and human tissues in culture. Our projects span regeneration, embryogenesis, cancer, and learning plasticity – all examples of how cellular networks process information. In all of these efforts, our goal is not only to understand the molecular mechanisms necessary for morphogenesis, but also to uncover and exploit the cooperative signaling dynamics that enable complex bodies to build and remodel themselves toward a correct structure. Our major goal is to understand how individual cell behaviors are orchestrated towards appropriate large-scale outcomes despite unpredictable environmental perturbations.
An ambitious study in yeast shows that the health of cells depends on the highly intertwined effects of many genes, few of which can be deleted together without consequence.
There could be some interesting data to play with here if available.
I also can’t help but wonder about applying some of Stuart Kauffman’s ideas to something like this. In particular, this sounds very reminiscent to his analogy of what happens when one strings thread randomly among a pile of buttons and the resulting complexity.Syndicated copies to:
Study in bacteria shows how regularly DNA changes and how few of those changes are deadly
This is a rather cool little experiment.
h/t to @moorejh via Twitter:
— Jason H. Moore, PhD (@moorejh) March 16, 2018
Bookmarked on March 16, 2018 at 12:15PMSyndicated copies to:
What is life? When Erwin Schrödinger posed this question in 1944, in a book of the same name, he was 57 years old. He had won the Nobel in Physics eleven years earlier, and was arguably past his glory days. Indeed, at that time he was working mostly on his ill-fated “Unitary Field Theory.” By all accounts, the publication of “What is Life?”—venturing far outside of a theoretical physicist’s field of expertise—raised many eyebrows. How presumptuous for a physicist to take on one of the deepest questions in biology! But Schrödinger argued that science should not be compartmentalized: “Some of us should venture to embark on a synthesis of facts and theories, albeit with second-hand and incomplete knowledge of some of them—and at the risk of making fools of ourselves.” Schrödinger’s “What is Life” has been extraordinarily influential, in one part because he was one of the first who dared to ask the question seriously, and in another because it was the book that was read by a good number of physicists—famously both Francis Crick and James Watson independently, but also many a member of the “Phage group,” a group of scientists that started the field of bacterial genetics—and steered them to new careers in biology. The book is perhaps less famous for the answers Schrödinger suggested, as almost all of them have turned out to be wrong.
Highlights, Quotes, & Marginalia
our existence can succinctly be described as “information that can replicate itself,” the immediate follow-up question is, “Where did this information come from?”
from an information perspective, only the first step in life is difficult. The rest is just a matter of time.
Through decades of work by legions of scientists, we now know that the process of Darwinian evolution tends to lead to an increase in the information coded in genes. That this must happen on average is not difficult to see. Imagine I start out with a genome encoding n bits of information. In an evolutionary process, mutations occur on the many representatives of this information in a population. The mutations can change the amount of information, or they can leave the information unchanged. If the information changes, it can increase or decrease. But very different fates befall those two different changes. The mutation that caused a decrease in information will generally lead to lower fitness, as the information stored in our genes is used to build the organism and survive. If you know less than your competitors about how to do this, you are unlikely to thrive as well as they do. If, on the other hand, you mutate towards more information—meaning better prediction—you are likely to use that information to have an edge in survival.
There are some plants with huge amounts of DNA compared to their “peers”–perhaps these would be interesting test cases for potential experimentation of this?Syndicated copies to:
A summer school for advanced undergraduates June 11-22, 2018 @ Princeton University What would it mean to have a physicist’s understanding of life? How do DYNAMICS and the EMERGENCE of ORDER affect biological function? How do organisms process INFORMATION, LEARN, ADAPT, and EVOLVE? See how physics problems emerge from thinking about developing embryos, communicating bacteria, dynamic neural networks, animal behaviors, evolution, and more. Learn how ideas and methods from statistical physics, simulation and data analysis, optics and microscopy connect to diverse biological phenomena. Explore these questions, tools, and concepts in an intense two weeks of lectures, seminars, hands-on exercises, and projects.
The International Conference on Complex Systems is a unique interdisciplinary forum that unifies and bridges the traditional domains of science and a multitude of real world systems. Participants will contribute and be exposed to mind expanding concepts and methods from across the diverse field of complex systems science. The conference will be held July 22-27, 2018, in Cambridge, MA, USA. Special Topic - Artificial Intelligence: This year’s conference will include a day on AI, including its development and potential future. This session will be chaired by Iyad Rahwan of MIT's Media Lab.
A great looking conference coming up with a strong line up of people who’s work I appreciate. It could certainly use some more balance however as it’s almost all white men.
In particular I’d want to see:
Albert-László Barabási (Northeastern University, USA)
Nassim Nicholas Taleb (Real World Risk Institute, USA)
Stuart Kauffman (Institute for Systems Biology, USA)
Simon DeDeo (Carnegie Mellon University, USA)
Stephen Wolfram (Wolfram Research)
César Hidalgo (MIT Media Lab, USA)
Marta González (University of California Berkeley, USA)
Peter Turchin (University of Connecticut, USA)
Mercedes Pascual (University of Chicago, USA) Pending confirmation
Iyad Rahwan (MIT Media Lab, USA)
Sandy Pentland (MIT Media Lab, USA)
Theresa Whelan (U.S. Department of Defense) Pending DOD approval
H. Eugene Stanley (Boston University, USA)
Ricardo Hausmann (Harvard University, USA)
Stephen Grossberg (Boston University, USA)
Daniela Rus (MIT Computer Science & Artificial Intelligence Lab, USA) Pending confirmation
Olaf Sporns (Indiana University Network Science Institute, USA)
Michelle Girvan (University of Maryland, USA) Pending confirmation
Cameron Kerry (MIT Media Lab, USA)
Irving Epstein (Brandeis University, USA)
DNA as a data storage medium has several advantages, including far greater data density compared to electronic media. We propose that schemes for data storage in the DNA of living organisms may benefit from studying the reconstruction problem, which is applicable whenever multiple reads of noisy data are available. This strategy is uniquely suited to the medium, which inherently replicates stored data in multiple distinct ways, caused by mutations. We consider noise introduced solely by uniform tandem-duplication, and utilize the relation to constant-weight integer codes in the Manhattan metric. By bounding the intersection of the cross-polytope with hyperplanes, we prove the existence of reconstruction codes with greater capacity than known error-correcting codes, which we can determine analytically for any set of parameters.
📖 Read Chapter 1: What is Life? pages 19-52 in The Vital Question: Energy, Evolution, and the Origins of Complex Life by (W.W. Norton,
, ISBN: 978-0393088816)
Lane lays out a “brief” history of the 4 billion years of life on Earth. Discusses isotopic fractionation and other evidence that essentially shows a bottleneck between bacteria and archaea (procaryotes) on the one hand and eucaryotes on the other, the latter of which all must have had a single common ancestor based on the genetic profiles we currently see. He suggest that while we should see even more diversity of complex life, we do not, and he hints at the end of the chapter that the reason is energy.
In general, it’s much easier to follow than I anticipated it might be. His writing style is lucid and fluid and he has some lovely prose not often seen in books of this sort. It’s quite a pleasure to read. Additionally he’s doing a very solid job of building an argument in small steps.
I’m watching closely how he’s repeatedly using the word information in his descriptions, and it seems to be a much more universal and colloquial version than the more technical version, but something interesting may come out of it from my philosophical leanings. I can’t wait to get further into the book to see how things develop.Syndicated copies to:
📗 Started reading pages 1-18 Introduction: Why is Life the Way it is in The Vital Question: Energy, Evolution, and the Origins of Complex Life by
A quick, but interesting peek into where he intends to go. He lays out some quick background here in the opening. He’s generally a very lucid writer so far. Can’t wait to get in further.
Some may feel like some of the terminology is a hurdle in the opening, so I hope he circles around to define some of his terms a bit better for the audience I suspect he’s trying to reach.Syndicated copies to:
All living things are made of cells, and all cells are powered by electrochemical charges across thin lipid membranes — the ‘proton motive force.’ We know how these electrical charges are generated by protein machines at virtually atomic resolution, but we know very little about how membrane bioenergetics first arose. By tracking back cellular evolution to the last universal common ancestor and beyond, scientist Nick Lane argues that geologically sustained electrochemical charges across semiconducting barriers were central to both energy flow and the formation of new organic matter — growth — at the very origin of life. Dr. Lane is a professor of evolutionary biochemistry in the Department of Genetics, Evolution and Environment at University College London. His research focuses on how energy flow constrains evolution from the origin of life to the traits of complex multicellular organisms. He is a co-director of the new Centre for Life’s Origins and Evolution (CLOE) at UCL, and author of four celebrated books on life’s origins and evolution. His work has been recognized by the Biochemical Society Award in 2015 and the Royal Society Michael Faraday Prize in 2016.
According to Google Scholar, Turing's paper inventing modern computing is only his _second_ most cited paper pic.twitter.com/T1M4k4dMYK
— michael_nielsen (@michael_nielsen) October 7, 2015
Looks like Alan Turing, like Claude Shannon, was interested in microbiology too! I’ll have to dig into this. [pdf]
As the ultimate information processing device, the brain naturally lends itself to be studied with information theory. Application of information theory to neuroscience has spurred the development of principled theories of brain function, has led to advances in the study of consciousness, and to the development of analytical techniques to crack the neural code, that is to unveil the language used by neurons to encode and process information. In particular, advances in experimental techniques enabling precise recording and manipulation of neural activity on a large scale now enable for the first time the precise formulation and the quantitative test of hypotheses about how the brain encodes and transmits across areas the information used for specific functions. This Special Issue emphasizes contributions on novel approaches in neuroscience using information theory, and on the development of new information theoretic results inspired by problems in neuroscience. Research work at the interface of neuroscience, Information Theory and other disciplines is also welcome. A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory". Deadline for manuscript submissions: 1 December 2017
Take chemistry, add energy, get life. The first tests of Jeremy England’s provocative origin-of-life hypothesis are in, and they appear to show how order can arise from nothing.
Interesting article with some great references I’ll need to delve into and read.
The situation changed in the late 1990s, when the physicists Gavin Crooks and Chris Jarzynski derived “fluctuation theorems” that can be used to quantify how much more often certain physical processes happen than reverse processes. These theorems allow researchers to study how systems evolve — even far from equilibrium.
I want to take a look at these papers as well as several about which the article is directly about.
Any claims that it has to do with biology or the origins of life, he added, are “pure and shameless speculations.”
Some truly harsh words from his former supervisor? Wow!
maybe there’s more that you can get for free
Most of what’s here in this article (and likely in the underlying papers) sounds to me to have been heavily influenced by the writings of W. Loewenstein and S. Kauffman. They’ve laid out some models/ideas that need more rigorous testing and work, and this seems like a reasonable start to the process. The “get for free” phrase itself is very S. Kauffman in my mind. I’m curious how many times it appears in his work?Syndicated copies to: