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Conference Paper: A modified entropy approach for construction of probabilistic boolean networks
Title  A modified entropy approach for construction of probabilistic boolean networks 

Authors  
Keywords  Genetic Regulatory Networks Sparse Probabilistic Boolean Networks Inverse Problem L(alpha)morm 
Issue Date  2010 
Publisher  Beijing World Publishing Corporation. The Journal's web site is located at http://www.aporc.org/LNOR/ 
Citation  Fourth International Conference on Computational Systems Biology (ISB2010), Suzhou, China, September 911, 2010. In Lecture Notes in Operations Research, 2010, v. 13, p. 243250 How to Cite? 
Abstract  Boolean Network (BN) and its extension Probabilistic Boolean network (PBN) have received much attention in modeling genetic regulatory networks. In this paper, we consider the problem of constructing a PBN from a given positive stationary distribution. The problem can be divided into two subproblems: Construction of a PBN from a given sparse transition probability matrix and construction of a sparse transition matrix from a given stationary distribution. These are inverse problems of huge sizes and we proposed mathematical models based on entropy theory. To obtain a sparse solution, we consider a new objective function having an addition term of Lanorm. Newton’s method in conjunction with CG method is then applied to solve the inverse problem. Numerical examples are given to demonstrate the effectiveness of our proposed method. 
Persistent Identifier  http://hdl.handle.net/10722/128313 
DC Field  Value  Language 

dc.contributor.author  Chen, X  en_HK 
dc.contributor.author  Li, L  en_HK 
dc.contributor.author  Ching, WK  en_HK 
dc.contributor.author  Tsing, NK  en_HK 
dc.date.accessioned  20101031T14:18:27Z   
dc.date.available  20101031T14:18:27Z   
dc.date.issued  2010  en_HK 
dc.identifier.citation  Fourth International Conference on Computational Systems Biology (ISB2010), Suzhou, China, September 911, 2010. In Lecture Notes in Operations Research, 2010, v. 13, p. 243250   
dc.identifier.uri  http://hdl.handle.net/10722/128313   
dc.description.abstract  Boolean Network (BN) and its extension Probabilistic Boolean network (PBN) have received much attention in modeling genetic regulatory networks. In this paper, we consider the problem of constructing a PBN from a given positive stationary distribution. The problem can be divided into two subproblems: Construction of a PBN from a given sparse transition probability matrix and construction of a sparse transition matrix from a given stationary distribution. These are inverse problems of huge sizes and we proposed mathematical models based on entropy theory. To obtain a sparse solution, we consider a new objective function having an addition term of Lanorm. Newton’s method in conjunction with CG method is then applied to solve the inverse problem. Numerical examples are given to demonstrate the effectiveness of our proposed method.   
dc.language  eng  en_HK 
dc.publisher  Beijing World Publishing Corporation. The Journal's web site is located at http://www.aporc.org/LNOR/   
dc.relation.ispartof  Lecture Notes in Operations Research   
dc.subject  Genetic Regulatory Networks   
dc.subject  Sparse Probabilistic Boolean Networks   
dc.subject  Inverse Problem   
dc.subject  L(alpha)morm   
dc.title  A modified entropy approach for construction of probabilistic boolean networks  en_HK 
dc.type  Conference_Paper  en_HK 
dc.identifier.email  Chen, X: dlkcissy@hotmail.com  en_HK 
dc.identifier.email  Li, L: liminli321@msn.com  en_HK 
dc.identifier.email  Ching, WK: wching@HKUCC.hku.hk  en_HK 
dc.identifier.email  Tsing, NK: nktsing@hku.hk  en_HK 
dc.description.nature  link_to_OA_fulltext   
dc.identifier.hkuros  179081  en_HK 
dc.identifier.volume  13  en_HK 
dc.identifier.spage  243   
dc.identifier.epage  250   