User:Yeem/urop

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UROP student: Michael Yee
Term: IAP 2007
Direct supervisor: Reshma Shetty
Faculty supervisor: Drew Endy

Drafted: Thursday 11 January 2007

An inverter is a logical device representing the Boolean NOT gate, a system whose output signal is the inverse of its input signal; a low input is converted to a high output and vice versa. In electrical circuits, the inverter is composed of combinations of transistors and diodes whose operation is characterized by properties such as “gain” and “swing”. These provide a measure of the reliability and efficiency of the inverter in question, as well as a way to compare similar devices; ideally, the system would exhibit minimal latency and noise with perfect switching behavior for the relevant range of input signals.

Our research focuses on porting the digital logic inverter to biological systems such as the bacteria Escherichia coli. Whereas the electrical circuit inverter operates via modulation of voltage, its biological equivalent consists of a repressor-operator system with rate of RNA polymerases as its signal carrier.

I will work closely with Reshma Shetty in the Knight Lab to help develop a computational model to simulate the operation of a genetically encoded inverter. The project requires the use of the SimBiology, a MATLAB toolbox that assists in the stochastic simulation of biological systems. Through careful analysis of ensemble computations, my goal is to calculate optimal values for the various parameters which affect the operation of the aforementioned device. Chief among these are the binding constants that dictate the affinity of intermolecular interactions in a contained volume such as the interior of a bacterial cell. By the end of IAP, I hope to have a flexible and fully functional simulation for the behavior of a genetically encoded inverter.

Most of my studies at MIT have focused on biological engineering, as my declared major is Course 20. Several of my courses have dealt with the subject of synthetic biology, or the manipulation of biological systems for novel engineering applications; in two of these classes, we specifically studied interchangeable biological devices such as the genetically encoded inverter. I am excited to be working on this project, as I can apply the concepts and skills that I developed in the classroom towards cutting-edge research at a world-class institution.

Of the available UROP positions at the Institute, I feel that I am most qualified for this project. In particular, this opportunity allows me to use my knowledge of programming in conjunction with my understanding of the underlying operation of complex biological systems to further develop connections between the two fields. Such a combination would help make me a valuable asset in the consideration of other opportunities in the future, both in the realm of computational biology and beyond, in the expanded scope of science and engineering jobs outside of my education at MIT.