article · 2014
Continuous Dynamic Bayesian Network for gene regulatory network modelling
Norhaini Baba, Mohd Saberi Mohamad, Abdul Hakim Mohamed Salleh, Mohd Hanafi Ahmad Hijazi, Lian En Chai, Muhammad Mahfuz Zainuddin, Safaai Deris
Cited by 5Abstract and details only
Abstract
In order to understand the underlying function of organisms, it is necessary to study the behaviour of genes in a gene regulatory network context. Several computational approaches are available for modelling gene regulatory networks with different datasets. Hence, this research is conducted to model the gene regulatory gene network using the proposed computational approach which is the Dynamic Bayesian Network. Dynamic Bayesian Network (DBN) is extensively used to construct GRNs based on its ability to handle microarray data and modelling feedback loops (cyclic regulation). The DBN approach is then extended to the continuous Dynamic Bayesian Network (cDBN) to construct a gene regulatory network with continuous data without discretization. The performance of the constructed gene networks of Saccharomyces cerevisiae were evaluated and compared with the previous works. At the end of this research, the gene networks constructed for Saccharomy cescerevisiae discovered more potential interactions between genes. Therefore, it can be concluded that the performance of the gene regulatory networks constructed using continuous dynamic Bayesian networks in this research is proven to be better because it can reveal more gene relationships as well as allowing feedback loops or cyclic regulation.
Cite this paper
Baba, N., Mohamad, M. S., Salleh, A. H. M., Hijazi, M. H. A., Chai, L. E., Zainuddin, M. M., & Deris, S. (2014). Continuous Dynamic Bayesian Network for gene regulatory network modelling. https://doi.org/10.1109/iccst.2014.7045200
Baba, Norhaini, et al. “Continuous Dynamic Bayesian Network for gene regulatory network modelling.” vol. 104, 2014, pp. 1–5, https://doi.org/10.1109/iccst.2014.7045200.
Baba, Norhaini, Mohd Saberi Mohamad, Abdul Hakim Mohamed Salleh, Mohd Hanafi Ahmad Hijazi, Lian En Chai, Muhammad Mahfuz Zainuddin, and Safaai Deris. 2014. “Continuous Dynamic Bayesian Network for gene regulatory network modelling.” https://doi.org/10.1109/iccst.2014.7045200.
Baba, N. et al. (2014) ‘Continuous Dynamic Bayesian Network for gene regulatory network modelling’. Available at: https://doi.org/10.1109/iccst.2014.7045200.
@article{baba2014continuous,
title = {{Continuous Dynamic Bayesian Network for gene regulatory network modelling}},
author = {Baba, Norhaini and Mohamad, Mohd Saberi and Salleh, Abdul Hakim Mohamed and Hijazi, Mohd Hanafi Ahmad and Chai, Lian En and Zainuddin, Muhammad Mahfuz and Deris, Safaai},
volume = {104},
pages = {1--5},
year = {2014},
doi = {10.1109/iccst.2014.7045200}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.