TY - GEN
T1 - An excursion through quantitative model refinement
AU - Azimi, Sepinoud
AU - Czeizler, Eugen
AU - Gratie, Cristian
AU - Gratie, Diana
AU - Iancu, Bogdan
AU - Ibssa, Nebiat
AU - Petre, Ion
AU - Rogojin, Vladimir
AU - Shadbahr, Tolou
AU - Shokri, Fatemeh
PY - 2015
Y1 - 2015
N2 - 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).
AB - 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).
UR - https://www.scopus.com/pages/publications/84955285481
U2 - 10.1007/978-3-319-28475-0_3
DO - 10.1007/978-3-319-28475-0_3
M3 - Conference contribution
AN - SCOPUS:84955285481
SN - 9783319284743
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 25
EP - 47
BT - Membrane Computing - 16th International Conference, CMC 2015, Revised Selected Papers
A2 - Sempere, José M.
A2 - Salomaa, Arto
A2 - Zandron, Claudio
A2 - Rozenberg, Grzegorz
PB - Springer
T2 - 16th International Conference on Membrane Computing, CMC 2015
Y2 - 17 August 2015 through 21 August 2015
ER -