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I'm interested in the evolution of complexity in biological systems. How did something as complex as the cell self-assemble?
It has been proposed that one of the main sources of this complexity comes from the combinatorially immense number
of possible interactions between the many molecules, especially proteins, that make up the cell. I have used a graph theory approach to model molecular interaction networks in the cell and am interested in pursuing a machine learning approach to predicting molecular interactions, the elements of biological networks. Specifically, I am interested in building tools that will allow me to study the differences between known signal transduction networks in different organisms and be able to predict new networks. Knowing how cell signaling systems evolve should help us understand the organizing principles behind them. Understanding signal transduction networks is vitally important to our understanding of disease and cell biology. If you have Internet Explorer 5 or above on Windows, click here. |
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