Hybrid-Controlled Neurofuzzy Networks Analysis Resulting in Genetic Regulatory Networks Reconstruction
Joint Authors
Aliyari Shoorehdeli, Mahdi
Malboobi, Mohammad Ali
Manshaei, Roozbeh
Feizi, Amir
Sobhe Bidari, Pooya
Lohrasebi, Tahmineh
Alirezaie, Javad
Kyan, Matthew
Source
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-11-01
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Reverse engineering of gene regulatory networks (GRNs) is the process of estimating genetic interactions of a cellular system from gene expression data.
In this paper, we propose a novel hybrid systematic algorithm based on neurofuzzy network for reconstructing GRNs from observational gene expression data when only a medium-small number of measurements are available.
The approach uses fuzzy logic to transform gene expression values into qualitative descriptors that can be evaluated by using a set of defined rules.
The algorithm uses neurofuzzy network to model genes effects on other genes followed by four stages of decision making to extract gene interactions.
One of the main features of the proposed algorithm is that an optimal number of fuzzy rules can be easily and rapidly extracted without overparameterizing.
Data analysis and simulation are conducted on microarray expression profiles of S.
cerevisiae cell cycle and demonstrate that the proposed algorithm not only selects the patterns of the time series gene expression data accurately, but also provides models with better reconstruction accuracy when compared with four published algorithms: DBNs, VBEM, time delay ARACNE, and PF subjected to LASSO.
The accuracy of the proposed approach is evaluated in terms of recall and F-score for the network reconstruction task.
American Psychological Association (APA)
Manshaei, Roozbeh& Sobhe Bidari, Pooya& Aliyari Shoorehdeli, Mahdi& Feizi, Amir& Lohrasebi, Tahmineh& Malboobi, Mohammad Ali…[et al.]. 2012. Hybrid-Controlled Neurofuzzy Networks Analysis Resulting in Genetic Regulatory Networks Reconstruction. ISRN Bioinformatics،Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-470738
Modern Language Association (MLA)
Manshaei, Roozbeh…[et al.]. Hybrid-Controlled Neurofuzzy Networks Analysis Resulting in Genetic Regulatory Networks Reconstruction. ISRN Bioinformatics No. 2012 (2012), pp.1-16.
https://search.emarefa.net/detail/BIM-470738
American Medical Association (AMA)
Manshaei, Roozbeh& Sobhe Bidari, Pooya& Aliyari Shoorehdeli, Mahdi& Feizi, Amir& Lohrasebi, Tahmineh& Malboobi, Mohammad Ali…[et al.]. Hybrid-Controlled Neurofuzzy Networks Analysis Resulting in Genetic Regulatory Networks Reconstruction. ISRN Bioinformatics. 2012. Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-470738
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-470738