Gene Regulatory Network Construction Parallel Technique Based on Network Component Analysis

2020 ◽  
pp. 850-857
Author(s):  
Dina Elsayad ◽  
Safwat Hamad ◽  
Howida A. Shedeed ◽  
Mohamed F. Tolba
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Component Analysis ◽  
Network Component Analysis ◽  
Network Construction ◽  
Gene Regulatory ◽  
Network Component ◽  
Parallel Technique

Hybrid High-Performance Computing Algorithm for Gene Regulatory Network

2021 ◽  
Vol 13 (1) ◽  
pp. 52-64
Author(s):  
Dina Elsayad ◽  
Safawat Hamad ◽  
Howida Abd-Alfatah Shedeed ◽  
Mohamed Fahmy Tolba
Keyword(s):  
High Performance Computing ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
High Performance ◽  
Network Inference ◽  
Component Analysis ◽  
Gene Regulatory Network Inference ◽  
Network Construction ◽  
Gene Regulatory ◽  
Performance Computing

This paper presents a parallel algorithm for gene regulatory network construction, hereby referred to as H2pcGRN. The construction of gene regulatory network is a vital methodology for investigating the genes interactions' topological order, annotating the genes functionality and demonstrating the regulatory process. One of the approaches for gene regulatory network construction techniques is based on the component analysis method. The main drawbacks of component analysis-based algorithms are its intensive computations that consume time. Despite these drawbacks, this approach is widely applied to infer the regulatory network. Therefore, introducing parallel techniques is indispensable for gene regulatory network inference algorithms. H2pcGRN is a hybrid high performance-computing algorithm for gene regulatory network inference. The proposed algorithm is based on both the hybrid parallelism architecture and the generalized cannon's algorithm. A variety of gene datasets is used for H2pcGRN assessment and evaluation. The experimental results indicated that H2pcGRN achieved super-linear speedup, where its computational speedup reached 570 on 256 processing nodes.

scholarly journals A Review of Integration Strategies to Support Gene Regulatory Network Construction

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Hailin Chen ◽  
Vincent VanBuren
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Data Sources ◽  
Second Phase ◽  
Network Construction ◽  
Structural Integration ◽  
Analytic Integration ◽  
Gene Regulatory ◽  
Two Phases ◽  
Integration Strategies

Gene regulatory network (GRN) construction is a central task of systems biology. Integration of different data sources to infer and construct GRNs is an important consideration for the success of this effort. In this paper, we will discuss distinctive strategies of data integration for GRN construction. Basically, the process of integration of different data sources is divided into two phases: the first phase is collection of the required data and the second phase is data processing with advanced algorithms to infer the GRNs. In this paper these two phases are called “structural integration” and “analytic integration,” respectively. Compared with the nonintegration strategies, the integration strategies perform quite well and have better agreement with the experimental evidence.

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