A system architecture for parallel analysis of flux-balanced metabolic pathways. (October 2020)

• Record Type: Journal Article
• Authors: Arabzadeh, Mona; Sedighi, Mehdi; Saheb Zamani, Morteza; Marashi, Sayed-Amir
• Is Part Of: Computational biology and chemistry. Volume 88(2020)
• Publication Date: 2020-10
• Subjects: Elementary flux mode (EFM) -- Graph data model -- Graphics processing unit (GPU) -- Metabolic pathways; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2020.107309
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: Proposing a modular system architecture to calculate minimal flux-balanced metabolic pathways. The architecture is based on the AND/OR graph model. The proposed architecture was implemented on a GPU platform to take advantage of the parallel architecture provided in the GPU based on multiple cores and hierarchical memory. The topology-based parallelism obtained by the system was the main achievement of the model. The simplified metabolic network of the CHO cell was studied to prove the concept of the design on metabolic networks to find EFMs. Besides, the potential of the model was studied on shortest pathways of the E. coli model. Abstract: Elementary flux mode (EFM) analysis is a well-studied method in constraint-based modeling of metabolic networks. In EFM analysis, a network is decomposed into minimal functional pathways based on the assumption of balanced metabolic fluxes. In this paper, a system architecture is proposed that approximately models the functionality of metabolic networks. The AND/OR graph model is used to represent the metabolic network and each processing element in the system emulates the functionality of a metabolite. The system is implemented on a graphics processing unit (GPU) as the hardware platform using CUDA environment. The proposed architecture takes advantage of the inherent parallelism in the network structure in terms of both pathway and metabolite traversal. The function of each element is defined such that it can find flux-balanced pathways. Pathways in both small and large metabolic networks are applied to the proposed architecture and the results are discussed.