A0302
Title: Boolean function networks
Authors: Maria Simak - Academia Sinica and National Chiao Tung University (Taiwan) [presenting]
Chen-Hsiang Yeang - Academia Sinica (Taiwan)
Jinn-Moon Yang - National Chiao Tung University (Taiwan)
Henry Horng-Shing Lu - National Yang Ming Chiao Tung University, Taiwan (Taiwan)
Abstract: A Boolean Function Network (BFN) model is developed by the integrated approach with the hidden Markov model (HMM), likelihood ratio tests and Boolean logic functions. We evaluate the performance of BFN through the applications to S. cerevisiae and the other biologic time course data. The BFN can produce regulatory relations that are mostly consistency with literature. In addition, it improves sensitivity and specificity with low computational complexity. Moreover, the Boolean functions discovered by BFN can provide useful biological insights for the control mechanisms of regulatory processes.
