NDLI: Inferring Fuzzy Cognitive Map models for Gene Regulatory Networks from gene expression data

Content Provider	IEEE Xplore Digital Library
Author	Ye Chen Mazlack, L.J. Lu, L.J.
Copyright Year	2012
Description	Author affiliation: School of Electronics and Computing Systems, University of Cincinnati, Cincinnati, OH, United States (Ye Chen) \|\| Applied Computational Intelligence Laboratory, University of Cincinnati, Cincinnati, OH, United States (Mazlack, L.J.) \|\| Division of Biomedicai Informatics, Cincinnati Children's Hospital, Medical Center Cincinnati, OH, United States (Lu, L.J.)
Abstract	Gene Regulatory Networks (GRNs) represent the causal relations among the genes and provide insight on the cellular functions and the mechanism of the diseases. GRNs can be inferred from gene expression data by a number of algorithms, e.g. Boolean networks, Bayesian networks, and differential equations. While reliable inference of GRNs is still an open problem, new algorithms need to be developed. Fuzzy Cognitive Maps (FCMs) is used to represent GRNs in this paper. Most of the FCM learning algorithms are able to learn FCMs with less than 40 nodes. A new algorithm that is able to learn FCMs with more than 100 nodes is proposed. The proposed method is based on Ant Colony Optimization (ACO). A decomposed approach is proposed to reduce the dimension of the problem; therefore the FCM learning algorithm is more scalable (the dimension of the problem to be solved in one ACO run equals to the number of nodes or genes). The proposed approach is tested on data from DREAM project. The experiment results suggest the proposed approach outperforms several other algorithms.
Starting Page	1
Ending Page	4
File Size	1744685
Page Count	4
File Format	PDF
ISBN	9781467325592
e-ISBN	9781467325608
e-ISBN	9781467325585
DOI	10.1109/BIBM.2012.6392627
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	learning algorithm Heuristic algorithms Bayesian methods Biological system modeling ant colony optimization Fuzzy cognitive maps Differential equations Inference algorithms Gene expression fuzzy cognitive map gene regulatory network gene expression
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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