The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Intelligent Framework With Controlled Behavior for Gene Regulatory Network Reconstruction
|
|
Author(s): Bhavana Bansal (Jaypee Institute of Information Technology, Noida, India), Aparajita Nanda (Jaypee Institute of Information Technology, Noida, India)and Anita Sahoo (Jaypee Institute of Information Technology, Noida, India)
Copyright: 2022
Volume: 12
Issue: 1
Pages: 17
Source title:
International Journal of Information Retrieval Research (IJIRR)
Editor(s)-in-Chief: Zhongyu Lu (University of Huddersfield, UK)
DOI: 10.4018/IJIRR.2022010104
Purchase
|
Abstract
Gene Regulatory Networks (GRNs) are the pioneering methodology for finding new gene interactions getting insights of the biological processes using time series gene expression data. It remains a challenge to study the temporal nature of gene expression data that mimic complex non-linear dynamics of the network. In this paper, an intelligent framework of recurrent neural network (RNN) and swarm intelligence (SI) based Particle Swarm Optimization (PSO) with controlled behaviour has been proposed for the reconstruction of GRN from time-series gene expression data. A novel PSO algorithm enhanced by human cognition influenced by the ideology of Bhagavad Gita is employed for improved learning of RNN. RNN guided by the proposed algorithm simulates the nonlinear and dynamic gene interactions to a greater extent. The proposed method shows superior performance over traditional SI algorithms in searching biologically plausible candidate networks. The strength of the method is verified by analyzing the small artificial network and real data of Escherichia coli with improved accuracy.
Related Content
|
Upendra Kumar.
© 2024.
31 pages.
|
|
B. Subbulakshmi, C. Deisy, S. Parthasarathy.
© 2023.
21 pages.
|
|
Reshu Agarwal, Adarsh Dixit.
© 2023.
14 pages.
|
|
Diksha Malhotra, Rajesh Bhatia, Manish Kumar.
© 2023.
13 pages.
|
|
Vikram Singh.
© 2023.
22 pages.
|
|
Ravindra Kumar Singh.
© 2023.
21 pages.
|
|
S. L. Gupta, Niraj Mishra.
© 2022.
27 pages.
|
|
|