Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

 
 
DownloadE-Mail
  Reaction networks and kinetics of biochemical systems

Arceo, C. P. P., Jose, E. C., Lao, A. R., & Mendoza, E. R. (2017). Reaction networks and kinetics of biochemical systems. Mathematical biosciences, 283, 13-29. doi:10.1016/j.mbs.2016.10.004.

Item is

Externe Referenzen

einblenden:
ausblenden:
Beschreibung:
-
OA-Status:

Urheber

einblenden:
ausblenden:
 Urheber:
Arceo, Carlene Perpetua P.1, Autor
Jose, Editha C.1, Autor
Lao, Angelyn R.1, Autor
Mendoza, Eduardo R.2, Autor           
Affiliations:
1external, ou_persistent22              
2Oesterhelt, Dieter / Membrane Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565164              

Inhalt

einblenden:
ausblenden:
Schlagwörter: MULTISTATIONARITY; SUBSPACESLife Sciences & Biomedicine - Other Topics; Mathematical & Computational Biology; Chemical reaction network; Kinetics set; Complex factorizable kinetics; Power law kinetics; Kinetic subspace; Span surjective kinetics; Total representation; Total kinetic system; Embedded representation; Embedded kinetic system;
 Zusammenfassung: This paper further develops the connection between Chemical Reaction Network Theory (CRNT) and Biochemical Systems Theory (BST) that we recently introduced [1]. We first use algebraic properties of kinetic sets to study the set of complex factorizable kinetics CFK(N) on a CRN, which shares many characteristics with its subset of mass action kinetics. In particular, we extend the Theorem of Feinberg-Horn [9] on the coincidence of the kinetic and stoichiometric subsets of a mass action system to CF kinetics, using the concept of span surjectivity. We also introduce the branching type of a network, which determines the availability of kinetics on it and allows us to characterize the networks for which all kinetics are complex factorizable: A "Kinetics Landscape" provides an overview of kinetics sets, their algebraic properties and containment relationships. We then apply our results and those (of other CRNT researchers) reviewed in [1] to fifteen BST models of complex biological systems and discover novel network and kinetic properties that so far have not been widely studied in CRNT. In our view, these findings show an important benefit of connecting CRNT and BST modeling efforts. (C) 2016 Elsevier Inc. All rights reserved.

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 2016-11-042017-01
 Publikationsstatus: Erschienen
 Seiten: 17
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: ISI: 000393007100003
DOI: 10.1016/j.mbs.2016.10.004
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: Mathematical biosciences
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: New York : Elsevier
Seiten: - Band / Heft: 283 Artikelnummer: - Start- / Endseite: 13 - 29 Identifikator: ISSN: 0025-5564
CoNE: https://pure.mpg.de/cone/journals/resource/991042744490246