Esther: Introducing an Online Platform for Parameter
Identification of Boolean Networks

D 2013

Esther: Introducing an Online Platform for Parameter Identification of Boolean Networks

STRECK, Adam, Juraj KOLČÁK, Heike SIEBERT a David ŠAFRÁNEK

Základní údaje

Originální název

Esther: Introducing an Online Platform for Parameter Identification of Boolean Networks

Autoři

STRECK, Adam (203 Česká republika, domácí), Juraj KOLČÁK (703 Slovensko, domácí), Heike SIEBERT (276 Německo) a David ŠAFRÁNEK (203 Česká republika, garant, domácí)

Vydání

Heidelberg, Computational Methods in Systems Biology 11th International Conference, CMSB 2013, Klosterneuburg, Austria, September 22-24, 2013, Proceedings, od s. 257-258, 2 s. 2013

Nakladatel

Springer

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Impakt faktor

Impact factor: 0.402 v roce 2005

Kód RIV

RIV/00216224:14330/13:00070435

Organizační jednotka

Fakulta informatiky

ISBN

978-3-642-40707-9

ISSN

UT WoS

000342772500033

Klíčová slova anglicky

systems biology; boolean networks; model checking

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 27. 4. 2014 23:32, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

When trying to uncover the nature of gene regulatory and signaling networks, the modelers currently have a zoo of inference algorithms at their disposal. These algorithms are very useful for converting raw experimental data into mathematical models of various nature – from pure differential equations to very abstract, logical causal networks. However, the algorithms rarely permit refitting of the network based on new data, and further enhancements are commonly done by hand, with quality of the process dependent on the experience of the modeler. We are therefore focusing on development of an environment that works with high level causal models and allows for automated comparison of the properties of the model and the behavior measured or observed in the modeled system. Since we expect the models to have wide range of possible kinetic parameters, we also provide means of manipulating with sets of parametrizations of the model, e.g. their ranking w.r.t. dynamic properties, visualizations, automated filtering, set operations etc.

Návaznosti

EE2.3.20.0256, projekt VaV

Název: Vytvoření výzkumného týmu a mezinárodního konzorcia pro počítačový model buňky sinice

Citovat

STRECK, Adam, Juraj KOLČÁK, Heike SIEBERT a David ŠAFRÁNEK. Esther: Introducing an Online Platform for Parameter Identification of Boolean Networks. In A. Gupta. Computational Methods in Systems Biology 11th International Conference, CMSB 2013, Klosterneuburg, Austria, September 22-24, 2013, Proceedings. Heidelberg: Springer, 2013, s. 257-258. ISBN 978-3-642-40707-9.

@inproceedings{1135951,
   author = {Streck, Adam and Kolčák, Juraj and Siebert, Heike and Šafránek, David},
   address = {Heidelberg},
   booktitle = {Computational Methods in Systems Biology 11th International Conference, CMSB 2013, Klosterneuburg, Austria, September 22-24, 2013, Proceedings},
   editor = {A. Gupta},
   keywords = {systems biology; boolean networks; model checking},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Heidelberg},
   isbn = {978-3-642-40707-9},
   pages = {257-258},
   publisher = {Springer},
   title = {Esther: Introducing an Online Platform for Parameter Identification of Boolean Networks},
   year = {2013}
}

TY  - JOUR
ID  - 1135951
AU  - Streck, Adam - Kolčák, Juraj - Siebert, Heike - Šafránek, David
PY  - 2013
TI  - Esther: Introducing an Online Platform for Parameter Identification of Boolean Networks
PB  - Springer
CY  - Heidelberg
SN  - 9783642407079
KW  - systems biology
KW  - boolean networks
KW  - model checking
N2  - When trying to uncover the nature of gene regulatory and signaling networks, the modelers currently have a zoo of inference algorithms at their disposal. These algorithms are very useful for converting raw experimental data into mathematical models of various nature – from pure differential equations to very abstract, logical causal networks. However, the algorithms rarely permit refitting of the network based on new data, and further enhancements are commonly done by hand, with quality of the process dependent on the experience of the modeler. We are therefore focusing on development of an environment that works with high level causal models and allows for automated comparison of the properties of the model and the behavior measured or observed in the modeled system. Since we expect the models to have wide range of possible kinetic parameters, we also provide means of manipulating with sets of parametrizations of the model, e.g. their ranking w.r.t. dynamic properties, visualizations, automated filtering, set operations etc.
ER  -

STRECK, Adam, Juraj KOLČÁK, Heike SIEBERT a David ŠAFRÁNEK. Esther: Introducing an Online Platform for Parameter Identification of Boolean Networks. In A. Gupta. \textit{Computational Methods in Systems Biology 11th International Conference, CMSB 2013, Klosterneuburg, Austria, September 22-24, 2013, Proceedings}. Heidelberg: Springer, 2013, s.~257-258. ISBN~978-3-642-40707-9.

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