Cancer as a Complex Adaptive System

Heng, et al recently published a review paper that brings together and touches on many different aspects of cancer complexity.  I thought this an opportunity to selectively quote the paper and organize the quotes loosely around various complex systems concepts they relate to.  I’m curious whether this makes sense to readers of this blog, or whether there’s too much unexplained jargon and too many large conceptual leaps.  Please ask questions or make comments freely below.

One preface I think will help is to understand that genome, karyotype and chromosome refer roughly to the same thing.  Here are several schematics that I will present without explanation that together illustrate how genes relate to genome/karyotype/chromosome structure, and how that in turn relates to the so-called genetic network (loosely equivalent to the “proteome”).  Of course “gene” is an outdated and inaccurate concept, so don’t get too hung up looking for genes here, just understand that they are sub-structural elements of the genome.

From MSU website

Best Reader Comment Award

I’m giving my “2009 Q1 award for most concise, lucid comment” to Paul Phillips for this gem:

Viewed from a thousand miles, the financial system has a incalculably large incentive to fail catastrophically as frequently as it can do so without killing the goose that lays the golden eggs.

As long as there is such a thing as “too big to fail” and trillions of dollars are available for siphoning, according to what logic can this cycle be dampened? Nobody has to explicitly pursue this outcome (although there are many who will) for it to be inevitable; the system obeys its own logic above all else.

[ commenting on Alfred Hubler on Stabilizing CAS ]

The Good, The Bad & The Ugly

A few articles on the economy that were sent my way recently.

The Good: After Capitalism (Geoff Mulgan)

The era of transition that we are entering will be disruptive—but it may bring a world where markets are servants, not masters.”  I urge you to read this entire article, and leave your ideological biases at the door.  Despite the title, this is no polemic.  Here’s the punchline:

Contemporary biology and social science has confirmed just how much we are social animals—dependent on others for our happiness, our self-respect, our worth and even our life. There is no inherent contradiction between capitalism and community. But we have learned that these connections are not automatic: they have to be cultivated and rewarded, and societies that invest large proportions of their surpluses on advertising to persuade people that individual consumption is the best route to happiness end up paying a high price.

Alfred Hubler on Stabilizing CAS

With his permission, I am posting an email thread between myself and Alfred Hubler.  I had contacted him on the recommendation of John Miller when Kevin and I were posting on the possibility of dampening boom-bust cycles in the financial markets through policy or other mechanisms.  Here’s what Hubler had to say:…

Another Must Read on the Origins of the Crisis

Steven Gjerstad and Vernon Smith have published a really nice article that starts out with bubbles in general and goes on to explain why the bursting of this particular bubble hurt the economy so much.  It echoes a lot of themes that I’ve covered before, but is obviously much more soundly though out.

The short version is that the effect of a bubble on the economy is determined by its effect on consumer spending.  The Dot Com Bubble didn’t have much of an effect because it primarily affected institutions and already relatively wealthy consumers. However, the Fed’s attempt to shorten the resulting recession created a loose monetary policy which forced dollars into the most attractive asset class: homes.  This attractiveness stemmed from relaxed lending standards and tax-free capital gains on homes, which created more buyers. But asset appreciation in this class is fundamentally limited by the ability of consumers to repay loans from income, which was not growing fast enough. As the institutions insuring mortgages …

Radical Transparency

In a March 2009 Wired article, Daniel Roth calls for radical transparency in financial reporting as the path to recovery and a more secure financial system.  He argues that the reporting requirements today allow companies to obscure what’s going on and that the way to fix things is as follows.   Embrace a markup language with which bite-sized chunks of standardly defined pieces of financial data are thrown out to the world so that users can crowdsource the true picture of a company’s financial health.…

Chasing the Dragon

Kevin just posted about a great article by Felix Salmon in Wired.  I underlined three quotes in my reading of it:

  1. “Correlation trading has spread through the psyche of the financial markets like a highly infectious thought virus.” (Tavakoli)
  2. “…the real danger was created not because any given trader adopted it but because every trader did. In financial markets, everybody doing the same thing is the classic recipe for a bubble and inevitable bust.” (Salmon)
  3. “Co-association between securities is not measurable using correlation…. Anything that relies on correlation is charlatanism.” (Taleb)

Superorganism and Singularity

There is an aspect to The Singularity which is not discussed much, an orthogonal dimension that is already taking shape, and which is perhaps more significant than what is implied by the “standard definition”:

The Singularity represents an “event horizon” in the predictability of human technological development past which present models of the future may cease to give reliable answers, following the creation of strong AI or the enhancement of human intelligence.  (Definition taken from The Singularity Summit website)

Complex Systems Defend Themselves

I’ve talked on here about the importance of taking seriously the notion of agency as it applies to systems other than biological.  In reading a recent Wired retrospective on what they called wrong, I was struck by feeling that their error was the same in all three cases, and that is underestimating the degree to which complex systems will defend themselves in the face of attack as if they were living, breathing organisms.…

Types of Emergence

Stability can be thought of as a measure of agency. That is, the more stable a system is, the better we are able to recognize it as a distinct agent, a system that actively, structurally or by happenstance persists through time, space and/or other dimensions. Burton Voorhees defines a concept of virtual stability as a “state in which a system employs self-monitoring and adaptive control to maintain itself in a configuration that would otherwise be unstable.” He clarifies that virtual stability is not the same as stability or metastability and gives formal definitions of all three.* By making a distinction between stability, metastability and virtual stability, we can gain further clarity on agency itself and the emergence of new agents and new levels of organization.…

Inter-Level Interactions

For me, the following metaphor really helps to envision the relationship between levels and their interactions. Imagine a clear rectangular container viewed from the side. Inside the container are various substances with various degrees of attraction to and repulsion from one another, such as sand, water, vegetable oil, alcohol, pebbles, ice, motor oil, etc. …

Mechanisms of Agency

The following is a non-exhaustive catalog. Note that these mechanisms are in fact emergent properties of the system under study, a fact which has some fairly profound consequences when considering the lowest known levels in physical systems. Read Ervin Laszlo’s chapter, Aspects of Information, in Evolution of Information Processing Systems (EIPS) for more theoretical background.


The most trivial form of stability we can think of is an agent existing in the same place over time without change. This may only make sense as you read on, so don’t get caught up here.


Keeping time in the equation but allowing physical location to vary, we see that agents can move and continue to exist and be recognized as the “same”. This is obvious in the physical world we live in, but consider what is going on with gliders in the Game of Life. The analogy is more than loose since cellular automata are network topologies which mirror physical space in one or two …