Presentation 2009-07-13
Uncorrelated inputs driven correlations in sub-Boolean networks
Chikoo OOSAWA,
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Abstract(in English) We propose an analyzing and comparing method for 12 different sub-Boolean networks that have three nodes. By applying random and uncorrelated binary external inputs to the 3-node sub-Boolean networks we obtained networks' dynamic characteristics from the output states from the nodes. Size of entropy and degree of correlations between outputs (mutual information) are also obtained from the states. The dynamic characteristics are sensitive to both subnetwork structures and Boolean function assignments to node. The characteristics provide useful insight into understanding of relationships between dynamics of subnetworks and their structures. Average output probabilites of 12 sub-Boolean networks are equal after averaging all possible combinations of Boolean functions. Sizes of entropy show the same order in different sub-Boolean networks. However sizes of mutual information strongly depends on the network structures that commonly share divergent structure, is consistent with an importance of gene duplications in evolutionary processes of gene networks.
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Keyword(in English) subnetwork / entropy / mutual information / network evolution
Paper # NLP2009-25,NC2009-18
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Committee NC
Conference Date 2009/7/6(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Uncorrelated inputs driven correlations in sub-Boolean networks
Sub Title (in English)
Keyword(1) subnetwork
Keyword(2) entropy
Keyword(3) mutual information
Keyword(4) network evolution
1st Author's Name Chikoo OOSAWA
1st Author's Affiliation Department of Bioscience & Bioinformatics, Kyushu Institute of Technology()
Date 2009-07-13
Paper # NLP2009-25,NC2009-18
Volume (vol) vol.109
Number (no) 125
Page pp.pp.-
#Pages 6
Date of Issue