Quantitative model refinement in four different frameworks, with applications to the heat shock response

Diana-Elena Gratie; Bogdan Iancu; Sepinoud Azimi Rashti; Ion Petre

doi:10.1201/b20053-20

Quantitative model refinement in four different frameworks, with applications to the heat shock response

Diana-Elena Gratie, Bogdan Iancu, Sepinoud Azimi Rashti, Ion Petre

Solutions for Health

Research output: Chapter in Book/Conference proceeding › Chapter › Scientific › peer-review

3 Citations (Scopus)

Abstract

Quantitative model refinement is an essential step in the model development cycle. Starting with a high level, abstract representation of a biological system, one often needs to add details to this representation to reflect changes in its constituent elements. Any such refinement step has two aspects: one structural and one quantitative. The structural aspect of the refinement defines an increase in the resolution of its representation, while the quantitative one specifies a numerical setup for the model that ensures its fit preservation at every refinement step. We discuss in this paper the implementation of quantitative model refinement in four extensively used bio-modelling frameworks: ODE-based models, rule-based models, Petri net models, and guarded command language models, emphasizing the specificity for every model implementation. We argue that quantitative model refinement is framework-independent, being implementable in all chosen frameworks despite their different underlying modelling paradigms. Quantitative model refinement is an essential step in the model development cycle. Starting with a high level, abstract representation of a biological system, one often needs to add details to this representation to reflect changes in its constituent elements. Any such refinement step has two aspects: one structural and one quantitative. The structural aspect of the refinement defines an increase in the resolution of its representation, while the quantitative one specifies a numerical setup for the model that ensures its fit preservation at every refinement step. We discuss in this paper the implementation of quantitative model refinement in four extensively used bio-modelling frameworks: ODE-based models, rule-based models, Petri net models, and guarded command language models, emphasizing the specificity for every model implementation. We argue that quantitative model refinement is framework-independent, being implementable in all chosen frameworks despite their different underlying modelling paradigms.

Original language	Undefined/Unknown
Title of host publication	From Action Systems to Distributed Systems
Editors	Luigia Petre, Emil Sekerinski
Publisher	CRC Press
Pages	201–214
ISBN (Electronic)	978-1-4987-0159-4
ISBN (Print)	978-1-4987-0158-7
DOIs	https://doi.org/10.1201/b20053-20
Publication status	Published - 2016
MoE publication type	A3 Part of a book or another research book

Access to Document

10.1201/b20053-20

Cite this

@inbook{c46ff8e310ba471ab7aec1fc4654c313,

title = "Quantitative model refinement in four different frameworks, with applications to the heat shock response",

abstract = "Quantitative model refinement is an essential step in the model development cycle. Starting with a high level, abstract representation of a biological system, one often needs to add details to this representation to reflect changes in its constituent elements. Any such refinement step has two aspects: one structural and one quantitative. The structural aspect of the refinement defines an increase in the resolution of its representation, while the quantitative one specifies a numerical setup for the model that ensures its fit preservation at every refinement step. We discuss in this paper the implementation of quantitative model refinement in four extensively used bio-modelling frameworks: ODE-based models, rule-based models, Petri net models, and guarded command language models, emphasizing the specificity for every model implementation. We argue that quantitative model refinement is framework-independent, being implementable in all chosen frameworks despite their different underlying modelling paradigms. Quantitative model refinement is an essential step in the model development cycle. Starting with a high level, abstract representation of a biological system, one often needs to add details to this representation to reflect changes in its constituent elements. Any such refinement step has two aspects: one structural and one quantitative. The structural aspect of the refinement defines an increase in the resolution of its representation, while the quantitative one specifies a numerical setup for the model that ensures its fit preservation at every refinement step. We discuss in this paper the implementation of quantitative model refinement in four extensively used bio-modelling frameworks: ODE-based models, rule-based models, Petri net models, and guarded command language models, emphasizing the specificity for every model implementation. We argue that quantitative model refinement is framework-independent, being implementable in all chosen frameworks despite their different underlying modelling paradigms.",

author = "Diana-Elena Gratie and Bogdan Iancu and {Azimi Rashti}, Sepinoud and Ion Petre",

year = "2016",

doi = "10.1201/b20053-20",

language = "Odefinierat/ok{\"a}nt",

isbn = "978-1-4987-0158-7",

pages = "201–214",

editor = "Luigia Petre and Emil Sekerinski",

booktitle = "From Action Systems to Distributed Systems",

publisher = "CRC Press",

}

Quantitative model refinement in four different frameworks, with applications to the heat shock response. / Gratie, Diana-Elena; Iancu, Bogdan; Azimi Rashti, Sepinoud et al.
From Action Systems to Distributed Systems. ed. / Luigia Petre; Emil Sekerinski. CRC Press, 2016. p. 201–214.

Research output: Chapter in Book/Conference proceeding › Chapter › Scientific › peer-review

TY - CHAP

T1 - Quantitative model refinement in four different frameworks, with applications to the heat shock response

AU - Gratie, Diana-Elena

AU - Iancu, Bogdan

AU - Azimi Rashti, Sepinoud

AU - Petre, Ion

PY - 2016

Y1 - 2016

N2 - Quantitative model refinement is an essential step in the model development cycle. Starting with a high level, abstract representation of a biological system, one often needs to add details to this representation to reflect changes in its constituent elements. Any such refinement step has two aspects: one structural and one quantitative. The structural aspect of the refinement defines an increase in the resolution of its representation, while the quantitative one specifies a numerical setup for the model that ensures its fit preservation at every refinement step. We discuss in this paper the implementation of quantitative model refinement in four extensively used bio-modelling frameworks: ODE-based models, rule-based models, Petri net models, and guarded command language models, emphasizing the specificity for every model implementation. We argue that quantitative model refinement is framework-independent, being implementable in all chosen frameworks despite their different underlying modelling paradigms. Quantitative model refinement is an essential step in the model development cycle. Starting with a high level, abstract representation of a biological system, one often needs to add details to this representation to reflect changes in its constituent elements. Any such refinement step has two aspects: one structural and one quantitative. The structural aspect of the refinement defines an increase in the resolution of its representation, while the quantitative one specifies a numerical setup for the model that ensures its fit preservation at every refinement step. We discuss in this paper the implementation of quantitative model refinement in four extensively used bio-modelling frameworks: ODE-based models, rule-based models, Petri net models, and guarded command language models, emphasizing the specificity for every model implementation. We argue that quantitative model refinement is framework-independent, being implementable in all chosen frameworks despite their different underlying modelling paradigms.

AB - Quantitative model refinement is an essential step in the model development cycle. Starting with a high level, abstract representation of a biological system, one often needs to add details to this representation to reflect changes in its constituent elements. Any such refinement step has two aspects: one structural and one quantitative. The structural aspect of the refinement defines an increase in the resolution of its representation, while the quantitative one specifies a numerical setup for the model that ensures its fit preservation at every refinement step. We discuss in this paper the implementation of quantitative model refinement in four extensively used bio-modelling frameworks: ODE-based models, rule-based models, Petri net models, and guarded command language models, emphasizing the specificity for every model implementation. We argue that quantitative model refinement is framework-independent, being implementable in all chosen frameworks despite their different underlying modelling paradigms. Quantitative model refinement is an essential step in the model development cycle. Starting with a high level, abstract representation of a biological system, one often needs to add details to this representation to reflect changes in its constituent elements. Any such refinement step has two aspects: one structural and one quantitative. The structural aspect of the refinement defines an increase in the resolution of its representation, while the quantitative one specifies a numerical setup for the model that ensures its fit preservation at every refinement step. We discuss in this paper the implementation of quantitative model refinement in four extensively used bio-modelling frameworks: ODE-based models, rule-based models, Petri net models, and guarded command language models, emphasizing the specificity for every model implementation. We argue that quantitative model refinement is framework-independent, being implementable in all chosen frameworks despite their different underlying modelling paradigms.

U2 - 10.1201/b20053-20

DO - 10.1201/b20053-20

M3 - Kapitel

SN - 978-1-4987-0158-7

SP - 201

EP - 214

BT - From Action Systems to Distributed Systems

A2 - Petre, Luigia

A2 - Sekerinski, Emil

PB - CRC Press

ER -