Simulation of Biochemical Reactions

In 1977, Daniel T. Gillespie published the paper that in essence starts the work in my field. Titled "Exact stochastic simulation of coupled chemical reactions" this work lays the foundation for stochastically simulating chemistry. In a biochemical system, reactions occur at random. In order to properly model this system, we must express it in terms of probabilities. The Stochastic Simulation Algorithm, or SSA, is a simulation technique that involves concepts of Monte Carlo simulation and Markov Chains.

In essence, a set of reactions is expressed as matrix of probabilities. Each reaction is assigned a probability, based on the number of reactants available, the number required for the reaction, and the rate of the reaction. These probabilities are lined up on the zero to one interval. Then, a random number generator is used to "select" which reaction fires. The process repeats until an end condition or when all reactions can no longer occur. Often, the reactions for a system are simulated many times to get a "mean" response.

The formulas for the probability of a reaction occurring is as follows:

We calculate the alpha value for each reaction. Using these values, we can determine the probabilities that each reaction will fire. This system gets very complicated with large numbers of reactants and reactions.

Next blog entry about my research: I will give a basic example using this method.

"Adverntures in Synthetic Biology"

For anyone that is interested, there exists a comic that talks about the field of Synthetic Biology. It can be found here on the Nature website. The corresponding article is also very helpful in understanding the field. In fact, it was one of my references on my NSF Fellowship application.

The term Synthetic Biology is generally used when it applies to chemists, biologists, geneticists, and other lab grunts working on creating synthetic biological components. This means that they are either changing the DNA of bacteria or creating man-made proteins or some other process that requires a wet lab and advanced knowledge in genetics/biology/chemistry. These Synthetic Biologists take their knowledge in biology and use it to create new functionality.

My research is also lumped into the realm of synthetic biology, and we do the exact opposite. We take our knowledge of computing and other fields and use it to create models for new functionality. I am *not* a biologist, chemist, or geneticist. My knowledge only goes a small way beyond the intro classes I was required to take in my undergrad degree. The papers we write don't claim we know any of the biochemistry behind the research, but propose that the long-standing models used are sufficient proof that our computation would work in vivo.

The third side of Synthetic Biology runs right in the middle. There are researchers at MIT and other places that work on creating repositories of standard parts. This could be a set of reactions or a chain of DNA for E.Coli that performs a known function and could theoretically be used in another design. A Synthetic Biologist could feasibly go to one of these databases and pick the correct part for their project, "plug it in," and away they go.

Hopefully that made some sense. I'll go into detail about my research in specific later. Feel free to add comments if there are questions.