Reconstruction of Gene Regulatory Network from Gene Perturbation Data, Current Methods and Problems

ALI, SEMAN and MOHAMED SAIFULAMAN MOHAMED, SAID and SHARIFALLILAH, NORDIN and WINDDY, PINDAH (2016) Reconstruction of Gene Regulatory Network from Gene Perturbation Data, Current Methods and Problems. In: Fifth International Conference On Advances in Computing, Electronics and Electrical Technology - CEET 2016, 12-13 March,2016, Kuala Lumpur, Malaysia.

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Abstract

The inference of regulators is the core factor in interpreting the actual regulatory conditions in gene regulatory networks (GRNs). Various methods have been developed to reconstruct GRNs with the motivation of improving the accuracy and scalability of network inference. Thus, this study will brief the structure of GRNs, discuss current methods of GRNs reconstruction and problems when dealing with gene perturbation data. Most of the information gathered from bioinformatics and system biology literature. At the end of the study several of GRNs reconstruction methods will be reviewed and identified their problem when dealing with gene perturbation data. This study is useful as a reference to develop more accurate GRNs inference methods particular for gene perturbation data.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: gene regulatory network, reconstruction of gene regulatory networks (GRNs), gene expression data, gene perturbation, machine learning methods
Depositing User: Mr. John Steve
Date Deposited: 27 Mar 2019 12:11
Last Modified: 27 Mar 2019 12:11
URI: http://publications.theired.org/id/eprint/1004

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