Caitlin McCollister

REU in Bioinformatics: Summer 2010

Research and Report

This summer I'm working under the guidance of my mentor to study the structures of gene regulatory networks. It's a fascinating intersection of graph theory, probability and (of course) biology. I am focusing on the idea of "synthetic" gene networks: building computer simulations of networks of interacting genes and transcription factors. While the types and numbers of node connections that biologists have observed in real-world gene networks do not follow an easily-generated probability distribution, neither are they simply random. However, it would be of great benefit to the bioinformatics and genomics field if their structure was better understood so that researchers could generate and use thousands of such networks as a preliminary testing ground for hypotheses.

For my own involvement, I have been familiarizing myself with the graph theory capabilities of the software package Mathematica. My final research project is to write a Mathematica program that will "grow" synthetic networks in an iterative growth process, and examine the resulting network properties compared to simple random networks.

My final report is now available: Growth Processes for Synthetic Regulatory Networks.

You can view a PDF copy of my source code along with output from a demonstration run of the program. If you use the Mathematica software package, you can also download and run my source notebook itself.