Erin Taylor

About Me

I'm a Ph.D. student in Electrical & Computer Engineering at the University of Florida where I also completed my M.S. in ECE and B.S. in Computer Science. Since my research focus is on modeling gene networks, I currently work in a Biomedical Engineering lab under William Ogle (CSSS 2001).

I've worked on models in theoretical ecology with Robert Holt and for my Master's research, I developed a probabilistic framework for predicting reliability in unreliable nanoelectronic circuits [1]. Currently, I'm interested in developing gene networks models and making them accessible to experimentalists in the field.

My other interests include:

• Running
• Reading
• Music
• Yoga
• Nature

I look forward to meeting you all in June! Until then, check out my twitter updates: erinrt or email me: erinrt at gmail dot com

Questions

What are your main interests? Feel free to include a "pie in the sky" big idea!

Advances in biotechnology have given us a wealth of data about genes, proteins and chemical interactions but the complexity of biological pathways makes it impossible for researchers to reason about them without formal mathematical techniques. I'm interested in addressing this problem by building models of gene networks using everything from Boolean logic and Bayesian networks to plain old differential equations. I want to make these models accessible to experimentalists who can then use them to direct their own research more effectively.

I'd like to develop some form of modular modeling framework for gene networks that could be used in an genetic algorithm to evolve biochemical pathways based on data collected experimentally. Parameter estimation tools have addressed this problem to an extent, but the user must provide the basic network structure. My idea for this tool would be that it could provide both network structure and parameter estimates in a way that is both accessible to experimentalists and more informative than a dependency graph (i.e., Bayesian network).

What sorts of expertise can you bring to the group?

I'm familiar with various modeling frameworks: Boolean, Bayesian, and neural networks and with differential equation dynamics. I'm comfortable programming in Java and C and am proficient with Matlab and Octave. I also have some good programs for working with differential equations, Berkeley Madonna and XPPAUT.

What do you hope to get out of the CSSS?

I hope to learn some new mathematical techniques and broaden my knowledge about dynamical systems. I look forward to meeting some new colleagues and gaining some new perspectives on my research.

Do you have any possible projects in mind for the CSSS?

• See question 1 above
• Along with my own past research, several groups have worked on modeling unreliable nanoscale circuits. It might be interesting to apply these techniques to the process of human aging and determine some kind of 'reliability bounds' for humans.
• Build a network model of antibiotic resistance in global communities and use it to determine the best strategies for antibiotic use.