An excursion through quantitative model refinement

Sepinoud Azimi Rashti, Eugen Czeizler, Diana-Elena Gratie, Cristian Gratie, Bogdan Iancu, Ibssa Nebiat, Ion Petre, Vladimir Rogojin, Tolou Shadbahr, Fatima Shokri-Manninen

Research output: Chapter in Book/Conference proceedingConference contributionScientificpeer-review

Abstract

There is growing interest in creating large-scale computational models for biological process. One of the challenges in such a project is to fit and validate larger and larger models, a process that requires more high-quality experimental data and more computational effort as the size of the model grows. Quantitative model refinement is a recently proposed model construction technique addressing this challenge. It proposes to create a model in an iterative fashion by adding details to its species, and to fix the numerical setup in a way that guarantees to preserve the fit and validation of the model. In this survey we make an excursion through quantitative model refinement – this includes introducing the concept of quantitative model refinement for reaction-based models, for rule-based models, for Petri nets and for guarded command language models, and to illustrate it on three case studies (the heat shock response, the ErbB signaling pathway, and the self-assembly of intermediate filaments).
Original languageUndefined/Unknown
Title of host publicationMembrane Computing
EditorsGrzegorz Rozenberg, Arto Salomaa, José M. Sempere, Claudio Zandron
PublisherSpringer
Pages25–47
ISBN (Electronic)978-3-319-28475-0
ISBN (Print)978-3-319-28474-3
DOIs
Publication statusPublished - 2015
MoE publication typeA4 Article in a conference publication
Eventconference - XV European Congress of Ichthyology
Duration: 1 Jan 2015 → …

Conference

Conferenceconference
Period01/01/15 → …

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