Seminar | April 20 | 5:15-6:15 p.m. | 891 Evans Hall
Abdul Salam Jarrah, American University of Sharjah, and MSRI (2016-2017)
Inferring the topology and dynamic of gene regulatory networks from expression time-course data is one of the challenging problems in systems biology. Given time course experimental data, the objective is to identify the structure of the network as well as the rules of interaction among the genes of the network. However, even within the Boolean network framework, there usually are many Boolean networks that explain the available data, and identifying most-likely networks is of great interest. The so-called threshold Boolean networks (TBNs) have been used to model a variety of gene regulatory networks. In a TBN, the future state of each node is determined by a linear inequality of the current states of its neighbors in the network and a threshold. In this talk, I will present an algebraic framework to study the inference problem, and will discuss a new method for inferring all threshold Boolean networks from available time-course data.