Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
  Biochemical network models simplified by balanced truncation

Liebermeister, W., Baur, U., & klipp, E. (2005). Biochemical network models simplified by balanced truncation. FEBS Journal, 272(16), 4034-4043. doi:10.1111/j.1742-4658.2005.04780.x.

Item is

Dateien

einblenden: Dateien
ausblenden: Dateien
:
Liebermeister et al. - FEBS J.pdf (beliebiger Volltext), 685KB
Name:
Liebermeister et al. - FEBS J.pdf
Beschreibung:
-
OA-Status:
Sichtbarkeit:
Öffentlich
MIME-Typ / Prüfsumme:
application/pdf / [MD5]
Technische Metadaten:
Copyright Datum:
-
Copyright Info:
eDoc_access: PUBLIC
Lizenz:
-

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
Liebermeister, Wolfram1, Autor
Baur, Ulrike, Autor
klipp, Edda2, Autor           
Affiliations:
1Max Planck Society, ou_persistent13              
2Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433554              

Inhalt

einblenden:
ausblenden:
Schlagwörter: balanced truncation; biochemical reaction system; complexity reduction; metabolic model; modularity
 Zusammenfassung: Modelling of biochemical systems usually focuses on certain pathways, while the concentrations of so-called external metabolites are considered fixed. This approximation ignores feedback loops mediated by the environment, that is, via external metabolites and reactions. To achieve a more realistic, dynamic description that is still numerically efficient, we propose a new methodology: the basic idea is to describe the environment by a linear effective model of adjustable dimensionality. In particular, we (a) split the entire model into a subsystem and its environment, (b) linearize the environment model around a steady state, and (c) reduce its dimensionality by balanced truncation, an established method for large-scale model reduction. The reduced variables describe the dynamic modes in the environment that dominate its interaction with the subsystem. We compute metabolic response coefficients that account for complexity-reduced dynamics of the environment. Our simulations show that a dynamic environment model can improve the simulation results considerably, even if the environment model has been drastically reduced and if its kinetic parameters are only approximately known. The speed-up in computation gained by model reduction may become vital for parameter estimation in large cell models.

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 2005-08
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: eDoc: 272851
DOI: 10.1111/j.1742-4658.2005.04780.x
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: FEBS Journal
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 272 (16) Artikelnummer: - Start- / Endseite: 4034 - 4043 Identifikator: ISSN: 0014-2956