• Dynamics, Thermodynamics and Information Processing in Chemical Networks, 13-16 June 2017, Complex Systems and Statistical Mechanics Group, University of Luxembourg. Organized by Massimiliano Esposito and Matteo Polettini.

They write, “The idea of the workshop is to bring in contact a small number of high-profile research groups working at the frontier between physics and biochemistry, with particular emphasis on the role of Chemical Networks.”

I’m looking forward to this, in part because there will be a mix of speakers I’ve met, speakers I know but haven’t met, and speakers I don’t know yet. I feel like reminiscing a bit, and I hope you’ll forgive me these reminiscences, since if you try the links you’ll get an introduction to the interface between computation and chemical reaction networks.

]]>• Programming with Chemical Reaction Networks: Mathematical Foundations, Banff International Research Station, 8-13 June 2014.

Now the slides for his talk are available:

• David Soloveichik, U.C. San Francisco, The computational power of chemical reaction networks.

And now I’d like to tell you about three more talks!

]]>• Programming with Chemical Reaction Networks: Mathematical Foundations, Banff International Research Station, 8-13 June 2014.

]]>The answer to that question is known. Stochastic Petri Nets (and equivalently chemical reaction networks) are not Turing-powerful in the strict sense, essentially because of all the decidable properties of Petri Nets. However, they can approximate a Turing machine up to any fixed error bound, so they are ‘almost’ Turing-complete, or ‘Turing-complete-up-to-epsilon’. The error bound can be fixed independently of the length of the computation (which, being a Turing machine, is not going to be known ahead of time); in practice, that means progressively slowing down the computation to make it more accurate over time and to remain below the global error bound.

Note also that polymerization is a chemical operation that goes beyond the power of Stochastic Petri Nets and plain chemical reaction networks: if you can form unbounded polymers (like, e.g., DNA), you can use them as registers or tapes and obtain full Turing completeness, chemically (or, you might say ‘biochemically’ because that’s where the most interesting polymers are found). An unbounded polymer corresponds to an infinite set of reactions (a small set of reactions for each polymer length), i.e. to an ‘actually infinite program’ in the language of simple reaction networks. Infinite programs of course are no good for any notion of Turing computation, so you need to use a more powerful language for describing polymerization, that is, a language that has the equivalent of molecular binding/unbinding as a primitive. That kind of language can be found in Process Algebra.

So, in addition to the

Chemical-Reaction-Networks/ Stochastic-Petri-Nets/ Turing-Completeness-Up-To-Epsilon

connection, there is another connection between

‘Biochemical’-Reaction-Networks/ Stochastic-Process-Algebra/ Full-Turing-Completeness.

I hope to learn more at this workshop—maybe that will help me answer your question.

I would like to nudge the conversation in the direction of understanding what biologically important chemical reactions actually do. They do complicated things, but it may not be wise to call these things ‘computations’, because what they do is often more ‘sloppy’ than what a digital computer does, yet still ‘successful’ according to some rather subtle criterion of ‘success’ that’s ultimately Darwinian. I don’t think anyone knows how to make this precise yet—not precise enough for theorems, anyway.

Needless to say, these thoughts are not new to me.

]]>I hear you shouldn’t leave novels or other literature lying around outside—it attracts the grizzly bears.

]]>Just watch out for the grizzlies :)

]]>