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Discrete Dynamics in Nature and Society Volume 2019 ,2019-07-24
Convergence of a Belief Propagation Algorithm for Biological Networks
Research Article
Sang-Mok Choo 1 Young-Hee Kim 2
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DOI:10.1155/2019/9362179
Received 2019-04-02, accepted for publication 2019-06-24, Published 2019-06-24
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摘要

Constructing network models of biological systems is important for effective understanding and control of the biological systems. For the construction of biological networks, a stochastic approach for link weights has been recently developed by using experimental data and belief propagation on a factor graph. The link weights were variable nodes of the factor graph and determined from their marginal probability mass functions which were approximated by using an iterative scheme. However, there is no convergence analysis of the iterative scheme. In this paper, at first, we present a detailed explanation of the complicated multistep process step by step with a network of small size and artificial experimental data, and then we show a sufficient condition for the convergence of the iterative scheme. Numerical examples are given to illustrate the whole process and to verify our result.

授权许可

Copyright © 2019 Sang-Mok Choo and Young-Hee Kim. 2019
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

通讯作者

Young-Hee Kim.Ingenium College of Liberal Arts, Kwangwoon University, Seoul 01897, Republic of Korea, kw.ac.kr.yhkim@kw.ac.kr

推荐引用方式

Sang-Mok Choo,Young-Hee Kim. Convergence of a Belief Propagation Algorithm for Biological Networks. Discrete Dynamics in Nature and Society ,Vol.2019(2019)

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