A simulation model of glucose-insulin metabolism and implementation on OSG

Milad Ghiasi Rad; Aditya Immaneni; Megan McCabe; Massimiliano Pierobon; Juan Cui

doi:10.1109/BIBM.2017.8217939

A simulation model of glucose-insulin metabolism and implementation on OSG

Milad Ghiasi Rad, Aditya Immaneni, Megan McCabe, Massimiliano Pierobon, Juan Cui

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

Abstract

In this paper, we present the design and implementation of a stand-Alone tool for metabolic simulation and its deployment on the Open Science Grid (OSG). The case study model of glucose-insulin metabolism aims at the development of a real-time monitoring system that can assist patients with diabetes to handle their blood glucose profile and maintain healthy diet habit. This system is able to integrate custom-built SBML models along with users' food intake information and produces the estimation of ATP, Glucose, and Insulin for the given duration using numerical analysis and simulation. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation of any given biochemical models. After implementation on OSG, the results have demonstrated the effectiveness of numerical optimization for model selection and the feasibility of the proposed tool for the given metabolic simulation. The ATP-glucose and glucose-insulin correlations revealed by this tool can be promising for a variety of different application cases.

Original language	English (US)
Title of host publication	Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Editors	Illhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1832-1839
Number of pages	8
ISBN (Electronic)	9781509030491
DOIs	https://doi.org/10.1109/BIBM.2017.8217939
State	Published - Dec 15 2017
Event	2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States Duration: Nov 13 2017 → Nov 16 2017

Publication series

Name	Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume	2017-January

Other

Other	2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Country/Territory	United States
City	Kansas City
Period	11/13/17 → 11/16/17

Keywords

OSG
chemical reactions
enzymes
metabolic network simulation
metabolic pathways

ASJC Scopus subject areas

Biomedical Engineering
Health Informatics

Access to Document

10.1109/BIBM.2017.8217939

Cite this

Rad, M. G., Immaneni, A., McCabe, M., Pierobon, M., & Cui, J. (2017). A simulation model of glucose-insulin metabolism and implementation on OSG. In I. Yoo, J. H. Zheng, Y. Gong, X. T. Hu, C.-R. Shyu, Y. Bromberg, J. Gao, & D. Korkin (Eds.), Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 (pp. 1832-1839). (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2017.8217939

A simulation model of glucose-insulin metabolism and implementation on OSG. / Rad, Milad Ghiasi; Immaneni, Aditya; McCabe, Megan et al.
Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. ed. / Illhoi Yoo; Jane Huiru Zheng; Yang Gong; Xiaohua Tony Hu; Chi-Ren Shyu; Yana Bromberg; Jean Gao; Dmitry Korkin. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1832-1839 (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January).

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

Rad, MG, Immaneni, A, McCabe, M, Pierobon, M & Cui, J 2017, A simulation model of glucose-insulin metabolism and implementation on OSG. in I Yoo, JH Zheng, Y Gong, XT Hu, C-R Shyu, Y Bromberg, J Gao & D Korkin (eds), Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1832-1839, 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, Kansas City, United States, 11/13/17. https://doi.org/10.1109/BIBM.2017.8217939

Rad MG, Immaneni A, McCabe M, Pierobon M, Cui J. A simulation model of glucose-insulin metabolism and implementation on OSG. In Yoo I, Zheng JH, Gong Y, Hu XT, Shyu CR, Bromberg Y, Gao J, Korkin D, editors, Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1832-1839. (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017). doi: 10.1109/BIBM.2017.8217939

Rad, Milad Ghiasi ; Immaneni, Aditya ; McCabe, Megan et al. / A simulation model of glucose-insulin metabolism and implementation on OSG. Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. editor / Illhoi Yoo ; Jane Huiru Zheng ; Yang Gong ; Xiaohua Tony Hu ; Chi-Ren Shyu ; Yana Bromberg ; Jean Gao ; Dmitry Korkin. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1832-1839 (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017).

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AB - In this paper, we present the design and implementation of a stand-Alone tool for metabolic simulation and its deployment on the Open Science Grid (OSG). The case study model of glucose-insulin metabolism aims at the development of a real-time monitoring system that can assist patients with diabetes to handle their blood glucose profile and maintain healthy diet habit. This system is able to integrate custom-built SBML models along with users' food intake information and produces the estimation of ATP, Glucose, and Insulin for the given duration using numerical analysis and simulation. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation of any given biochemical models. After implementation on OSG, the results have demonstrated the effectiveness of numerical optimization for model selection and the feasibility of the proposed tool for the given metabolic simulation. The ATP-glucose and glucose-insulin correlations revealed by this tool can be promising for a variety of different application cases.

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A simulation model of glucose-insulin metabolism and implementation on OSG

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Keywords

ASJC Scopus subject areas

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