A 2-stage approach for inferring gene regulatory networks using dynamic Bayesian networks

Akther Shermin*, Mehmet A. Orgun

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

6 Citations (Scopus)
4 Downloads (Pure)

Abstract

The inference of Gene Regulatory networks (GRN) from microarrray data suffers from the low accuracy and the excessive computation time. Biological domain knowledge of the cellular process, from which the data is generated, is believed to be effective in addressing such challenges. In this paper, we have used two biological features of gene regulation of yeast cell cycle: 1) a high proportion of the Cell Cycle Regulated genes are periodically expressed, and 2) genes are both co-expressed and co-regulated. Together with the computational implementation of these features, we have learnt regulators of both individual and co-expressed genes using Dynamic Bayesian Networks. The proposed 2-stage GRN model has been found to be more computationally efficient and topologically accurate compared to other existing models.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009
Place of PublicationLos Alamitos, CA
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages166-169
Number of pages4
ISBN (Print)9780769538853
DOIs
Publication statusPublished - 2009
Event2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009 - Washington, D.C., United States
Duration: 1 Nov 20094 Nov 2009

Other

Other2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009
CountryUnited States
CityWashington, D.C.
Period1/11/094/11/09

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    Shermin, A., & Orgun, M. A. (2009). A 2-stage approach for inferring gene regulatory networks using dynamic Bayesian networks. In 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009 (pp. 166-169). [5341827] Los Alamitos, CA: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/BIBM.2009.87