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Network Completion for Static Gene Expression Data
Joint Authors
Nakajima, Natsu
Akutsu, Tatsuya
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-26
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Natural & Life Sciences (Multidisciplinary)
Biology
Abstract EN
We tackle the problem of completing and inferring genetic networks under stationary conditions from static data, where network completion is to make the minimum amount of modifications to an initial network so that the completed network is most consistent with the expression data in which addition of edges and deletion of edges are basic modification operations.
For this problem, we present a new method for network completion using dynamic programming and least-squares fitting.
This method can find an optimal solution in polynomial time if the maximum indegree of the network is bounded by a constant.
We evaluate the effectiveness of our method through computational experiments using synthetic data.
Furthermore, we demonstrate that our proposed method can distinguish the differences between two types of genetic networks under stationary conditions from lung cancer and normal gene expression data.
American Psychological Association (APA)
Nakajima, Natsu& Akutsu, Tatsuya. 2014. Network Completion for Static Gene Expression Data. Advances in Bioinformatics،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-467667
Modern Language Association (MLA)
Nakajima, Natsu& Akutsu, Tatsuya. Network Completion for Static Gene Expression Data. Advances in Bioinformatics No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-467667
American Medical Association (AMA)
Nakajima, Natsu& Akutsu, Tatsuya. Network Completion for Static Gene Expression Data. Advances in Bioinformatics. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-467667
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-467667