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 proceedingConference 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 languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
EditorsIllhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1832-1839
Number of pages8
ISBN (Electronic)9781509030491
DOIs
StatePublished - Dec 15 2017
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: Nov 13 2017Nov 16 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume2017-January

Other

Other2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
CountryUnited States
CityKansas City
Period11/13/1711/16/17

Fingerprint

Insulin
Metabolism
Glucose
Adenosinetriphosphate
Adenosine Triphosphate
Computer Systems
Feeding Behavior
Blood Glucose
Nutrition
Medical problems
Eating
Numerical analysis
Blood
Monitoring
Computer simulation

Keywords

  • OSG
  • chemical reactions
  • enzymes
  • metabolic network simulation
  • metabolic pathways

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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; Pierobon, Massimiliano; Cui, Juan.

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 proceedingConference 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 C-R, 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). https://doi.org/10.1109/BIBM.2017.8217939
Rad, Milad Ghiasi ; Immaneni, Aditya ; McCabe, Megan ; Pierobon, Massimiliano ; Cui, Juan. / 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).
@inproceedings{493c6e4523bb4274bcf85692144baa2b,
title = "A simulation model of glucose-insulin metabolism and implementation on OSG",
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.",
keywords = "OSG, chemical reactions, enzymes, metabolic network simulation, metabolic pathways",
author = "Rad, {Milad Ghiasi} and Aditya Immaneni and Megan McCabe and Massimiliano Pierobon and Juan Cui",
year = "2017",
month = "12",
day = "15",
doi = "10.1109/BIBM.2017.8217939",
language = "English (US)",
series = "Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1832--1839",
editor = "Illhoi Yoo and Zheng, {Jane Huiru} and Yang Gong and Hu, {Xiaohua Tony} and Chi-Ren Shyu and Yana Bromberg and Jean Gao and Dmitry Korkin",
booktitle = "Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017",

}

TY - GEN

T1 - A simulation model of glucose-insulin metabolism and implementation on OSG

AU - Rad, Milad Ghiasi

AU - Immaneni, Aditya

AU - McCabe, Megan

AU - Pierobon, Massimiliano

AU - Cui, Juan

PY - 2017/12/15

Y1 - 2017/12/15

N2 - 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.

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.

KW - OSG

KW - chemical reactions

KW - enzymes

KW - metabolic network simulation

KW - metabolic pathways

UR - http://www.scopus.com/inward/record.url?scp=85046083499&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85046083499&partnerID=8YFLogxK

U2 - 10.1109/BIBM.2017.8217939

DO - 10.1109/BIBM.2017.8217939

M3 - Conference contribution

AN - SCOPUS:85046083499

T3 - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

SP - 1832

EP - 1839

BT - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

A2 - Yoo, Illhoi

A2 - Zheng, Jane Huiru

A2 - Gong, Yang

A2 - Hu, Xiaohua Tony

A2 - Shyu, Chi-Ren

A2 - Bromberg, Yana

A2 - Gao, Jean

A2 - Korkin, Dmitry

PB - Institute of Electrical and Electronics Engineers Inc.

ER -