Bond-Graph Modelling and Causal Analysis of Biomolecular Systems

2017 ◽  
pp. 587-623 ◽  
Author(s):  
Peter J. Gawthrop
Keyword(s):  
Causal Analysis ◽  
Bond Graph ◽  
Biomolecular Systems

scholarly journals Modular Dynamic Biomolecular Modelling: The Unification of Stoichiometry, Thermodynamics, Kinetics and Data

2021 ◽  
Author(s):  
Peter J. Gawthrop ◽  
Michael Pan ◽  
Edmund J. Crampin
Keyword(s):  
Dynamic Models ◽  
System Development ◽  
Kinetic Modelling ◽  
Simulation Models ◽  
Bond Graph ◽  
Model Parameters ◽  
Biomolecular Systems ◽  
Genome Wide ◽  
Estimation Of Model Parameters ◽  
Genome Scale

AbstractRenewed interest in dynamic simulation models of biomolecular systems has arisen from advances in genome-wide measurement and applications of such models in biotechnology and synthetic biology. In particular, genome-scale models of cellular metabolism beyond the steady state are required in order to represent transient and dynamic regulatory properties of the system. Development of such whole-cell models requires new modelling approaches. Here we propose the energy-based bond graph methodology, which integrates stoichiometric models with thermo-dynamic principles and kinetic modelling. We demonstrate how the bond graph approach intrinsically enforces thermodynamic constraints, provides a modular approach to modelling, and gives a basis for estimation of model parameters leading to dynamic models of biomolecular systems. The approach is illustrated using a well-established stoichiometric model of E. coli and published experimental data.

scholarly journals Robust Diagnosis of Industrial Systems by Bond graph Model

2018 ◽  
Vol 7 (3.13) ◽  
pp. 55
Author(s):  
Abderrahmene Sellami ◽  
Dhia Mzoughi ◽  
Abdelkader Mami
Keyword(s):  
Hydraulic System ◽  
Graph Model ◽  
Research Problem ◽  
Causal Analysis ◽  
Bond Graph ◽  
Link Diagram ◽  
Linear Transformations ◽  
Sand Filter ◽  
Industrial Systems ◽  
Theoretical Results

This paper aims to solve a research problem by a robust diagnosis of a hydraulic system with sand filter by approach of graph of connection using fractional linear transformations (BG-LFT). The method we develop is based on the use of analytic redundant relations by a bond graph graph model (BG-ARRs). These relationships not only allow the detection and isolation of defects on the various elements of the system, but also the location by structural and causal analysis. The results suggest that the use of the link diagram model for a valve fault (eg an R1 valve is blocked), figures 9.a), 9.b) and 9.c) show that the residual models r1 and r2 become non-zero, so the flow and pressure levels are zero at reservoir C2. These values mean that these residues are sensitive to the variation of the flow rate at the level of the valve R1, which is confirmed by the theoretical results presented in table 2. The simulation of the system is carried out by the software dedicated to the bond graph approach 

scholarly journals Modular bond‐graph modelling and analysis of biomolecular systems

2016 ◽  
Vol 10 (5) ◽  
pp. 187-201 ◽  
Author(s):  
Peter J. Gawthrop ◽  
Edmund J. Crampin
Keyword(s):  
Bond Graph ◽  
Biomolecular Systems

scholarly journals Modular dynamic biomolecular modelling with bond graphs: the unification of stoichiometry, thermodynamics, kinetics and data

2021 ◽  
Vol 18 (181) ◽  
pp. 20210478
Author(s):  
Peter J. Gawthrop ◽  
Michael Pan ◽  
Edmund J. Crampin
Keyword(s):  
Dynamic Models ◽  
System Development ◽  
Kinetic Modelling ◽  
Simulation Models ◽  
Bond Graph ◽  
Model Parameters ◽  
Biomolecular Systems ◽  
Genome Wide ◽  
Estimation Of Model Parameters ◽  
Genome Scale

Renewed interest in dynamic simulation models of biomolecular systems has arisen from advances in genome-wide measurement and applications of such models in biotechnology and synthetic biology. In particular, genome-scale models of cellular metabolism beyond the steady state are required in order to represent transient and dynamic regulatory properties of the system. Development of such whole-cell models requires new modelling approaches. Here, we propose the energy-based bond graph methodology, which integrates stoichiometric models with thermodynamic principles and kinetic modelling. We demonstrate how the bond graph approach intrinsically enforces thermodynamic constraints, provides a modular approach to modelling, and gives a basis for estimation of model parameters leading to dynamic models of biomolecular systems. The approach is illustrated using a well-established stoichiometric model of Escherichia coli and published experimental data.

Design of a Ka Band Antenna by a New Methodology Based on Bond Graph Approach

2015 ◽  
Vol 5 (5) ◽  
pp. 301
Author(s):  
Sabri Jmal ◽  
Hichem Taghouti ◽  
Abdelkader Mami
Keyword(s):  
Bond Graph ◽  
Ka Band

Bond graph model of a PEM fuel cell stack

2008 ◽  
Vol 1 (06) ◽  
pp. 329-334
Author(s):  
S. Rabih ◽  
C. Turpin ◽  
S. Astier
Keyword(s):  
Fuel Cell ◽  
Graph Model ◽  
Pem Fuel Cell ◽  
Bond Graph ◽  
Fuel Cell Stack

The Impact of Business Mentoring on Micro, Small, Medium Enterprises Performance

2017 ◽  
Vol 1 (1) ◽  
pp. 31-37
Author(s):  
Mohammad Adrian ◽  
Hendrati Dwi Mulyaningsih ◽  
Santi Rahmawati
Keyword(s):  
Quantitative Research ◽  
Causal Analysis ◽  
Coefficient Of Determination ◽  
Mentoring Program ◽  
Simple Regression Analysis ◽  
Small Medium Enterprises ◽  
Medium Enterprises ◽  
The Impact ◽  
Necessity Entrepreneur ◽  
Simple Regression

This reasearch is conducted on MMSME (Micro Small Medium Enterprises) that are participated in the MMSME Syari’ah Mentoring Program by Academicians and Practitioners (PUSPA) organized by Bank Indonesia in Bandung. MMSME who participated in PUSPA program 2016 is MMSME that included in necessity entrepreneur where MMSME operated just to fullfil the life necessities. The purpose of this reasearch was to investigate the influence of the business mentoring on the MMSME performance in PUSPA program 2016. Researcher used quantitative research method. Data were analyzed using simple regression analysis and descriptive-causal analysis. The result showed that business mentoring affect the performance of MMSME that participated in PUSPA Program 2016. Based on the calculation, coefficient of determination (R2) can be seen the influence of business mentoring variable (X) on the performance (Y) is 74%. While the remaining 26% is influenced by other factors such as entrepreneurship competence and human resources.

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