Difference between revisions of "Team:Stanford-Brown/Modeling"

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Revision as of 02:50, 18 September 2015

Notebooks

Modeling an in silico alternative

Why Model?

Experimentation makes up the backbone of any scientific discipline, and synthetic biology is no exception. It is only through experimental analysis that we can understand, test, and refine our biological creations in a rigorous manner. One might be tempted to ask why computation and simulation need even make appearances on our stage. We shall attempt to say a few words in the defense of mathematical modeling.

To the question “Why model?”, Joshua Epstein, the 2008 recipient of the NIH Director’s Pioneer Award, offers a simple retort: “You are a modeler,” by which he means to say that we all are constantly running implicit models inside our head often without realizing it. When a PCR yields unexpected results, for example, we may call upon an internal model of DNA replication in order to assess the points at which reality may have diverged from expectation: perhaps the primers bound to the template DNA non-selectively or maybe our chosen annealing temperature was too high. Whenever scientists generate hypotheses based on some internal picture in their head, those scientists are practicing the age old tradition of modeling.

The question then becomes, “Why use mathematical models?” Our PCR example from above offers an answer to this question as well. In determining whether nonspecificity lay at the root of our faulty PCR, we may resort to a read-alignment program that can computationally predict potential primer binding sites. And it is standard practice to use an annealing-temperature calculator before designing a set of PCR cycles. The existence and widespread use of tools such as these illustrates the inadequacy of our minds in solving certain problems without aid as well as the consequent need for explicit quantitative models and computing machinery.

In the case of our project, we used computational tools to help model the molecular dynamics of two of our biosynthetic reactions. These were instances where human intuition alone could not reliably answer a question that interested us, namely, which enzyme (PAL or FDC) or substrate (CoA or Acetate) exerts greater control on the flux or amount of product in our specified pathway? It is this question that we shall explore below.

But how? with the following projects below

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Go write all your modeling stuff here

Polystyrene Engineering E. coli to produce polystyrene

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Polyhydroxyalkanoates Optimizing the production of biological PHA

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C.A.S.H. Cellulose Associated Spore HYDRAS, or a biological contractile mechanism

Based on work done by Chen et al. at Columbia university, we sought to employ the contractile properties of bacterial spores to use as a contractile mechanism for biOrigami.

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CRATER Crisper Assited Transformation Efficient Reaction

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