PAGeneRN: Parallel Architecture for Gene Regulatory Network

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Author(s): Dina Elsayad (Ain Shams University, Egypt), A. Ali (Ain Shams University, Egypt), Howida A. Shedeed (Ain Shams University, Egypt)and Mohamed F. Tolba (Ain Shams University, Egypt)
Copyright: 2017
Pages: 25
Source title: Handbook of Research on Machine Learning Innovations and Trends
Source Author(s)/Editor(s): Aboul Ella Hassanien (Cairo University, Egypt)and Tarek Gaber (Suez Canal University, Egypt)
DOI: 10.4018/978-1-5225-2229-4.ch034

Keywords: Artificial Intelligence / Computational Intelligence / Computer Science & IT / Information Science Reference

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Abstract

The gene expression analysis is an important research area of Bioinformatics. The gene expression data analysis aims to understand the genes interacting phenomena, gene functionality and the genes mutations effect. The Gene regulatory network analysis is one of the gene expression data analysis tasks. Gene regulatory network aims to study the genes interactions topological organization. The regulatory network is critical for understanding the pathological phenotypes and the normal cell physiology. There are many researches that focus on gene regulatory network analysis but unfortunately some algorithms are affected by data size. Where, the algorithm runtime is proportional to the data size, therefore, some parallel algorithms are presented to enhance the algorithms runtime and efficiency. This work presents a background, mathematical models and comparisons about gene regulatory networks analysis different techniques. In addition, this work proposes Parallel Architecture for Gene Regulatory Network (PAGeneRN).

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