Functional information and the emergence of biocomplexity

Journal club time again 🙂

I like this paper: Functional information and the emergence of biocomplexity by Hazen et al, 2007 in PNAS, and which I hadn’t been aware of.

I’ve only had time to skim it so far, but as it seems to be an interesting treatment of the concepts variously referred to by ID proponents as CSI, dFCSI, etc, I thought it might be useful.  It is also written with reference to AVIDA.  Here is the abstract:

Complex emergent systems of many interacting components, including complex biological systems, have the potential to perform quantifiable functions. Accordingly, we define “functional information,” I(Ex ), as a measure of system complexity. For a given system and function, x (e.g., a folded RNA sequence that binds to GTP), and degree of function, Ex (e.g., the RNA–GTP binding energy), I(Ex ) = −log2[F(E x)], where F(Ex ) is the fraction of all possible configurations of the system that possess a degree of function ≥ Ex . Functional information, which we illustrate with letter sequences, artificial life, and biopolymers, thus represents the probability that an arbitrary configuration of a system will achieve a specific function to a specified degree. In each case we observe evidence for several distinct solutions with different maximum degrees of function, features that lead to steps in plots of information versus degree of function.

I thought it would be interesting to look at following the thread on Abel’s paper.  I’d certainly be interested in hearing what our ID contributors make of it 🙂

 

155 thoughts on “Functional information and the emergence of biocomplexity

  1. Elizabeth: So, using their measure of Functional Complexity, they demonstrate that AVIDA, a program that uses Darwinian evolution to evolve virtual organisms, results in increases in Functional Complexity.
    So, where does this leave ID? Is this not prima facie evidence that Darwinian processes can do exactly what ID proponents say it can’t?

    I would approach this quite differently. Avida is basically the smooth road up mount improbable. Avida is a good model of genetic evolution only if it can be shown that complex biological systems (like the flagellum with all its special-purpose proteins and building instructions) can be accessed through naturalistic mutations and permutations of genetic code, using similar step-wise improvements. It’s the nature of the solution space that is important. Sure Avida “works” for its toy problem, and yes, I can get up the second floor taking one step at a time. If the “stairs” weren’t (or aren’t) there, it’s quite a different matter. It’s not the fact that changes in CSI aren’t observed in natural process, ID just says that for many biological problems, no smooth road or small steps, each one being functional and conferring some benefit — will ever be found — because it just doesn’t exist.

  2. Avida is a good model of genetic evolution only if it can be shown that complex biological systems (like the flagellum with all its special-purpose proteins and building instructions) can be accessed through naturalistic mutations and permutations of genetic code, using similar step-wise improvements.

    Well yes, evolution requires and assumes that step-wise change is possible. That’s what Lensky and Thornton (among others) have been testing. Some idea of the functional landscape, and whether it is connected, may be found here:

    http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0060085

    Evolution does not require that the path to be smooth or consistently uphill, or that every change be an improvement. It’s been 50 years since neutral theory was first formalized.

  3. petrushka: Evolution does not require that the path to be smooth or consistently uphill, or that every change be an improvement. It’s been 50 years since neutral theory was first formalized.

    Quite true. I was speaking in generalities. Yet the path must indeed exist, even if indirect, and the steps must not be so large or rare as to be “inaccessible” given the number of offspring available, the number of changes required, and probabilities involved.

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