NDLI: Reconstruction of Gene Regulatory Networks using Differential Evolution

Content Provider	IEEE Xplore Digital Library
Author	Mondal, B.S. Sarkar, A.K. Hasan, M.M. Noman, N.
Copyright Year	2010
Description	Author affiliation: Department of Computer Science and Engineering, Dhaka University, 1000, Bangladesh (Mondal, B.S.; Sarkar, A.K.; Hasan, M.M.; Noman, N.)
Abstract	Gene Regulatory Network (GRN) is an abstract mapping of gene regulations in living cells that can help to predict the system behavior of living organisms. In this research, we use a model based inference method to reconstruct GRN from gene expression data. We use linear time variant model which is of particular interest among all other models because of its capability of discovering the non-linear interactions among genes in a reasonably short time even while dealing with noisy time-series data. Here, Differential Evolution (DE), a versatile, robust and well-known Evolutionary Algorithm (EA) has been used. The potency of the proposed method has been verified in gene network reconstruction experiments, varying the network dimension and characteristics, the amount of gene expression data used for inference, and the noise level present in gene expression profiles. Real expression dataset of SOS DNA repair system in Escherichia coli is used to reconstruct the regulatory network. All these experiments have proved the efficacy of the proposed reconstruction method.
Starting Page	440
Ending Page	445
File Size	224692
Page Count	6
File Format	PDF
ISBN	9781424484966
e-ISBN	9781424484973
DOI	10.1109/ICCITECHN.2010.5723898
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-23
Publisher Place	Bangladesh
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Global optimization Noise Reverse engineering DNA Differential evolution Data models Mathematical model Gene expression Noise measurement Linear time variant model
Content Type	Text
Resource Type	Article

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