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| project SIAN | misc. | about |

First, we would like to thank Dr. Joe Song of New Mexico State University, without whom, none of this would be possible. He gave us inspiration and provided valuable ideas and sources that assisted us in our research and programming that has greatly helped us through the various stages of the project. His guidance as been invaluable. In addition we would like to thank Mr. Greg Marez for his unrelenting positive attitude and his sense of “coolness.” His humor propelled us through tough, bumpy roads throughout stages of the project. Finally, we would like to thank our parents for constantly providing encouragement and support through the entire research and programming processes; without their support, we may have never gone so far… [1] Lahdesmaki, H., Shmulevich, I., and Yli-Harja, O. "On Learning Gene Regulatory Networks Under the Boolean Network Model." Machine Learning, 52 (2003):147-167. [2] Liang, S., S. Fuhrman and R. Somogyi. “REVEAL, a general reverse engineering algorithm for inference of genetic network architecture.” Pacific Symposium on Biocomputing 3 (1998): 18–29. [3] Pal, R., I. Ivanov, A. Datta, M.L. Bittner and E.R. Dougherty. “Generating Boolean networks with a prescribed attractor structure.” Bioinformatics 21 (2005): 4021–4025. [4] Shmulevich, I., E.R. Dougherty, S. Kim and W. Zhang. “Probabilistic Boolean networks: rule-based uncertainty model for gene regulatory networks.” Bioinformatics 18 (2002): 261–274. [5] Shmulevich, I., Dougherty, E., and Zhang, W. "From Boolean to Probabilistic Boolean Networks as Models of Genetic Regulatory Networks." IEEE, 90 (2002): 1778-1792.