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Hokkaido University Collection of Scholarly and Academic Papers >
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Construction Method of Probabilistic Boolean Networks Based on Imperfect Information
This item is licensed under:Creative Commons Attribution 4.0 International
| Title: | Construction Method of Probabilistic Boolean Networks Based on Imperfect Information |
| Authors: | Umiji, Katsuaki Browse this author | | Kobayashi, Koichi Browse this author →KAKEN DB | | Yamashita, Yuh Browse this author →KAKEN DB |
| Keywords: | gene regulatory network | | linear programming | | matrix-based representation | | probabilistic Boolean network |
| Issue Date: | Dec-2019 |
| Publisher: | MDPI |
| Journal Title: | Algorithms |
| Volume: | 12 |
| Issue: | 12 |
| Start Page: | 268 |
| Publisher DOI: | 10.3390/a12120268 |
| Abstract: | A probabilistic Boolean network (PBN) is well known as one of the mathematical models of gene regulatory networks. In a Boolean network, expression of a gene is approximated by a binary value, and its time evolution is expressed by Boolean functions. In a PBN, a Boolean function is probabilistically chosen from candidates of Boolean functions. One of the authors has proposed a method to construct a PBN from imperfect information. However, there is a weakness that the number of candidates of Boolean functions may be redundant. In this paper, this construction method is improved to efficiently utilize given information. To derive Boolean functions and those selection probabilities, the linear programming problem is solved. Here, we introduce the objective function to reduce the number of candidates. The proposed method is demonstrated by a numerical example. |
| Rights: | https://creativecommons.org/licenses/by/4.0/ |
| Type: | article |
| URI: | http://hdl.handle.net/2115/76727 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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