学术报告-Wai-Ki CHING

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2018-10-15 09:36:00

学术报告

题      目:Boolean and Probabilistic Boolean Networks


报  告  人:Wai-Ki CHING     (邀请人:刘秋丽)

                                 香港大学


时      间:2018-10-15 16:30--17:30

地      点:学院401

报告人简介:

        香港大学数学系教授,曾经担任香港大学数学系主任。


摘      要:

      Boolean Networks (BNs) and its extension Probabilistic Boolean Networks (PBNs) are useful and effective tools for studying genetic regulatory networks. A PBN is essentially a collection of BNs driven by a Markov chain (a random process). A BN is characterized by its attractor cycles and a PBN is characterized by its steady-state distribution. We review some algorithms for finding attractor cycles and steady-state distributions for BNs and PBNs, respectively. We then discuss an inverse problem, the problem of constructing a PBN given a set of BNs. It is well-known that the control of a genetic regulatory network is useful for avoiding undesirable states associated with diseases and this results in a control problem. We formulate both problems as optimization problems and efficient algorithms are also presented to solve them. Other applications of PBNs will also be discussed.