🔖 Complexity: An interdisciplinary forum for complexity research | PLOS

Bookmarked Complexity: An interdisciplinary forum for complexity research by PLOS (channels.plos.org)

Most of today’s global challenges, from online misinformation spreading to Ebola outbreaks, involve such a vast number of interacting players that reductionism delivers little insight. Systems are often non-linear, exhibiting complexity in temporal and spatial domains over large scales, which is a challenge to predictability and comprehension. Strategies must be found to look at the problem as a whole, in all its complexity. Representing the associated data as a complex network, in which nodes and connections between them form complicated patterns, is one such strategy. Network science provides novel tools for analyzing, visualizing and modeling this data thanks to the cross-fertilization of fields as diverse as statistical physics, algebraic topology and machine learning, among the others.

This Channel brings together all aspects of complexity research and includes interdisciplinary topics from network theory to applications in neuroscience and the social sciences.

hat tip:

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🔖 NSF Workshop on Multidisciplinary Complex Systems Research – NSF Workshop on Multidisciplinary Complex Systems Research

Bookmarked NSF Workshop on Multidisciplinary Complex Systems Research – NSF Workshop on Multidisciplinary Complex Systems Research (nsfws.ece.drexel.edu)

This workshop will bring together a diverse group of experts in complementary areas of complex systems and will be preceded by a series of weekly webinars. The overarching goal of the activity is to address scientific issues that are relevant to the scientific community and bring to surface possible areas of opportunity for multidisciplinary research in the study of complex systems. The specific goals of the workshop include:

  1. identifying the most substantive research questions that can be addressed by fundamental complex systems research;
  2. recognizing community needs, knowledge gaps, and barriers to research progress in this area;
  3. identifying future directions that cut across disciplinary boundaries and that are likely to lead to transformative multidisciplinary research in complex systems.

The outcomes of the workshop will include the preparation of a report to inform the scientific community at large of the current status and challenges as well as future opportunities in multidisciplinary complex systems research as perceived by the participants of the workshop.

The workshop is motivated by the observation that many processes in natural, engineered, and social contexts exhibit emergent collective behavior and are thus governed by complex systems. Because challenges in understanding, predicting, designing, and controlling complex systems are often common to many domains, a central objective of the workshop is to facilitate the exchange of ideas across different fields and avoid disciplinary boundaries typical of many traditional scientific meetings. The workshop participants will include experts both in theory and in applications as well as a selection of postdoctoral researchers and graduate students from various domains. Because of the cross-disciplinary nature of the workshop, the participants themselves will become aware of the latest developments in fields related to but different from their own. This environment will foster discussions on the state of the art, potential issues, and most promising directions in multidisciplinary complex systems research. The inclusion of early-career researchers will help to promote the transfer of this expertise to the next generation of engineers, mathematicians, and scientists.

Downloadable [.pdf] copy of the report

h/t to @adilson_motter

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👓 Algorithmic Information Dynamics: A Computational Approach to Causality and Living Systems From Networks to Cells | Complexity Explorer | Santa Fe Institute

Read Algorithmic Information Dynamics: A Computational Approach to Causality and Living Systems From Networks to Cells (Complexity Explorer | Santa Fe Institute)

About the Course:

Probability and statistics have long helped scientists make sense of data about the natural world — to find meaningful signals in the noise. But classical statistics prove a little threadbare in today’s landscape of large datasets, which are driving new insights in disciplines ranging from biology to ecology to economics. It's as true in biology, with the advent of genome sequencing, as it is in astronomy, with telescope surveys charting the entire sky.

The data have changed. Maybe it's time our data analysis tools did, too.
During this three-month online course, starting June 11th, instructors Hector Zenil and Narsis Kiani will introduce students to concepts from the exciting new field of Algorithm Information Dynamics to search for solutions to fundamental questions about causality — that is, why a particular set of circumstances lead to a particular outcome.

Algorithmic Information Dynamics (or Algorithmic Dynamics in short) is a new type of discrete calculus based on computer programming to study causation by generating mechanistic models to help find first principles of physical phenomena building up the next generation of machine learning.

The course covers key aspects from graph theory and network science, information theory, dynamical systems and algorithmic complexity. It will venture into ongoing research in fundamental science and its applications to behavioral, evolutionary and molecular biology.

Students should have basic knowledge of college-level math or physics, though optional sessions will help students with more technical concepts. Basic computer programming skills are also desirable, though not required. The course does not require students to adopt any particular programming language for the Wolfram Language will be mostly used and the instructors will share a lot of code written in this language that student will be able to use, study and exploit for their own purposes.

Course Outline:

  • The course will begin with a conceptual overview of the field.
  • Then it will review foundational theories like basic concepts of statistics and probability, notions of computability and algorithmic complexity, and brief introductions to graph theory and dynamical systems.
  • Finally, the course explores new measures and tools related to reprogramming artificial and biological systems. It will showcase the tools and framework in applications to systems biology, genetic networks and cognition by way of behavioral sequences.
  • Students will be able apply the tools to their own data and problems. The instructors will explain  in detail how to do this, and  will provide all the tools and code to do so.

The course runs 11 June through 03 September 2018.

Tuition is $50 required to get to the course material during the course and a certificate at the end but is is free to watch and if no fee is paid materials will not be available until the course closes. Donations are highly encouraged and appreciated in support for SFI's ComplexityExplorer to continue offering  new courses.

In addition to all course materials tuition includes:

  • Six-month access to the Wolfram|One platform (potentially renewable by other six) worth 150 to 300 USD.
  • Free digital copy of the course textbook to be published by Cambridge University Press.
  • Several gifts will be given away to the top students finishing the course, check the FAQ page for more details.

Best final projects will be invited to expand their results and submit them to the journal Complex Systems, the first journal in the field founded by Stephen Wolfram in 1987.

About the Instructor(s):

Hector Zenil has a PhD in Computer Science from the University of Lille 1 and a PhD in Philosophy and Epistemology from the Pantheon-Sorbonne University of Paris. He co-leads the Algorithmic Dynamics Lab at the Science for Life Laboratory (SciLifeLab), Unit of Computational Medicine, Center for Molecular Medicine at the Karolinska Institute in Stockholm, Sweden. He is also the head of the Algorithmic Nature Group at LABoRES, the Paris-based lab that started the Online Algorithmic Complexity Calculator and the Human Randomness Perception and Generation Project. Previously, he was a Research Associate at the Behavioural and Evolutionary Theory Lab at the Department of Computer Science at the University of Sheffield in the UK before joining the Department of Computer Science, University of Oxford as a faculty member and senior researcher.

Narsis Kiani has a PhD in Mathematics and has been a postdoctoral researcher at Dresden University of Technology and at the University of Heidelberg in Germany. She has been a VINNOVA Marie Curie Fellow and Assistant Professor in Sweden. She co-leads the Algorithmic Dynamics Lab at the Science for Life Laboratory (SciLifeLab), Unit of Computational Medicine, Center for Molecular Medicine at the Karolinska Institute in Stockholm, Sweden. Narsis is also a member of the Algorithmic Nature Group, LABoRES.

Hector and Narsis are the leaders of the Algorithmic Dynamics Lab at the Unit of Computational Medicine at Karolinska Institute.

Alyssa Adams has a PhD in Physics from Arizona State University and studies what makes living systems different from non-living ones. She currently works at Veda Data Solutions as a data scientist and researcher in social complex systems that are represented by large datasets. She completed an internship at Microsoft Research, Cambridge, UK studying machine learning agents in Minecraft, which is an excellent arena for simple and advanced tasks related to living and social activity. Alyssa is also a member of the Algorithmic Nature Group, LABoRES.

The development of the course and material offered has been supported by: 

  • The Foundational Questions Institute (FQXi)
  • Wolfram Research
  • John Templeton Foundation
  • Santa Fe Institute
  • Swedish Research Council (Vetenskapsrådet)
  • Algorithmic Nature Group, LABoRES for the Natural and Digital Sciences
  • Living Systems Lab, King Abdullah University of Science and Technology.
  • Department of Computer Science, Oxford University
  • Cambridge University Press
  • London Mathematical Society
  • Springer Verlag
  • ItBit for the Natural and Computational Sciences and, of course,
  • the Algorithmic Dynamics lab, Unit of Computational Medicine, SciLifeLab, Center for Molecular Medicine, The Karolinska Institute

Class Introduction:Class IntroductionHow to use Complexity Explorer:How to use Complexity Explorer

Course dates: 11 Jun 2018 9pm PDT to 03 Sep 2018 10pm PDT


  1. A Computational Approach to Causality
  2. A Brief Introduction to Graph Theory and Biological Networks
  3. Elements of Information Theory and Computability
  4. Randomness and Algorithmic Complexity
  5. Dynamical Systems as Models of the World
  6. Practice, Technical Skills and Selected Topics
  7. Algorithmic Information Dynamics and Reprogrammability
  8. Applications to Behavioural, Evolutionary and Molecular Biology


Another interesting course from the SFI. Looks like an interesting way to spend the summer.

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🔖 Special Issue : Information Dynamics in Brain and Physiological Networks | Entropy

Bookmarked Special Issue "Information Dynamics in Brain and Physiological Networks" (mdpi.com)

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory".

Deadline for manuscript submissions: 30 December 2018

It is, nowadays, widely acknowledged that the brain and several other organ systems, including the cardiovascular, respiratory, and muscular systems, among others, exhibit complex dynamic behaviors that result from the combined effects of multiple regulatory mechanisms, coupling effects and feedback interactions, acting in both space and time.

The field of information theory is becoming more and more relevant for the theoretical description and quantitative assessment of the dynamics of the brain and physiological networks, defining concepts, such as those of information generation, storage, transfer, and modification. These concepts are quantified by several information measures (e.g., approximate entropy, conditional entropy, multiscale entropy, transfer entropy, redundancy and synergy, and many others), which are being increasingly used to investigate how physiological dynamics arise from the activity and connectivity of different structural units, and evolve across a variety of physiological states and pathological conditions.

This Special Issue focuses on blending theoretical developments in the new emerging field of information dynamics with innovative applications targeted to the analysis of complex brain and physiological networks in health and disease. To favor this multidisciplinary view, contributions are welcome from different fields, ranging from mathematics and physics to biomedical engineering, neuroscience, and physiology.

Prof. Dr. Luca Faes
Prof. Dr. Alberto Porta
Prof. Dr. Sebastiano Stramaglia
Guest Editors
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The Physics of Life: Summer School | Center for the Physics of Biological Function

Bookmarked The Physics of Life: Summer School | Center for the Physics of Biological Function (biophysics.princeton.edu)
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.
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Acquired A New Kind of Science by Stephen Wolfram (Wolfram Media)
Starting from a collection of simple computer experiments illustrated by striking computer graphics Stephen Wolfram shows in this landmark book how their unexpected results force a whole new way of looking at the operation of our universe. Wolfram uses his approach to tackle a remarkable array of fundamental problems in science, from the origins of apparent randomness in physical systems, to the development of complexity in biology, the ultimate scope and limitations of mathematics, the possibility of a truly fundamental theory of physics, the interplay between free will and determinism, and the character of intelligence in the universe.

Gifted to me by my friend Dave Snead who picked up a copy from the Wolfram booth earlier today at the APS Conference in downtown Los Angeles. Thanks Dave!

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🔖 NetSci 2018 11-15 June 2018 in Paris, France

Bookmarked NetSci 2018 (NetSci 2018)
NetSci 2018, the flagship conference of the Network Science Society, aims to bring together leading researchers and practitioners working in the emerging area of network science. The conference fosters interdisciplinary communication and collaboration in network science research across computer and information sciences, physics, mathematics, statistics, the life sciences, neuroscience, environmental sciences, social sciences, finance and business, arts and design. NetSci 2018 in Paris, France will be a combination of: * An International School for students and non-experts (June 11-12, 2018) * Satellite Symposia (June 11-12, 2018) * A 3-day Conference (June 13-15, 2018) featuring research in a wide range of topics and in different formats, including keynote and invited talks, oral presentations, posters, and lightning talks.

Registration Deadlines:
February 8: Registration opens.
March 20: Registration for presenters of accepted contributions ends.
April 10: Early registration ends.
May 28: Online registration ends.

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🔖 9th International Conference on Complex Systems | NECSI

Bookmarked 9th International Conference on Complex Systems | NECSI (necsi.edu)
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)

Others include:
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)

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📖 Read pages 19-52 of The Vital Question: Energy, Evolution, and the Origins of Complex Life by Nick Lane

📖 Read Chapter 1: What is Life? pages 19-52 in The Vital Question: Energy, Evolution, and the Origins of Complex Life by Nick Lane (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.

book cover of Nick Lane's The Vital Question
The Vital Question: Energy, Evolution and the Origins of Complex Life by Nick Lane
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📗 Started reading The Vital Question: Energy, Evolution, and the Origins of Complex Life by Nick Lane

📗 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 Nick Lane

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.

book cover of Nick Lane's The Vital Question
The Vital Question: Energy, Evolution and the Origins of Complex Life by Nick Lane
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Energy and Matter at the Origins of Life by Nick Lane | Santa Fe Institute

Bookmarked Energy and Matter at the Origin of Life by Nick Lane (Santa Fe Institute Community Event (YouTube))
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.

h/t Santa Fe Institute

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The Chemical Basis of Morphogenesis by Alan Turing

Reposted a tweet by Michael Nielsen (Twitter)

Looks like Alan Turing, like Claude Shannon, was interested in microbiology too! I’ll have to dig into this. [pdf]

👓 A 2017 Nobel laureate says he left science because he ran out of money and was fed up with academia | QZ

Read A 2017 Nobel laureate left science because he ran out of money (Quartz)
Jeffrey Hall, a retired professor at Brandeis University, shared the 2017 Nobel Prize in medicine for discoveries elucidating how our internal body clock works. He was honored along with Michael Young and his close collaborator Michael Roshbash. Hall said in an interview from his home in rural Maine that he collaborated with Roshbash because they shared...

This is an all-too-often heard story. The difference is that now a Nobel Prize winner is telling it about himself!

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SFI and ASU to offer online M.S. in Complexity | Complexity Explorer

Bookmarked SFI and ASU to offer online M.S. in Complexity (Complexity Explorer)
SFI and Arizona State University soon will offer the world’s first comprehensive online master’s degree in complexity science. It will be the Institute’s first graduate degree program, a vision that dates to SFI’s founding. “With technology, a growing recognition of the value of online education, widespread acceptance of complexity science, and in partnership with ASU, we are now able to offer the world a degree in the field we helped invent,” says SFI President David Krakauer, “and it will be taught by the very people who built it into a legitimate domain of scholarship.”
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