CRNreals

A toolbox for distinguishability and identifiability analysis of biochemical reaction networks

G. Szederkényi, Julio R. Banga, Antonio A. Alonso

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Chemical reaction network theory is widely used in modeling and analyzing complex biochemical systems such as metabolic networks and cell signalling pathways. Being able to produce all the biologically and chemically important qualitative dynamical features, chemical reaction networks (CRNs) have attracted significant attention in the systems biology community. It is well-known that the reliable inference of CRN models generally requires thorough identifiability and distinguishability analysis together with carefully selected prior modeling assumptions. Here, we present a software toolbox CRNreals that supports the distinguishability and identifiability analysis of CRN models using recently published optimization-based procedures.

Original languageEnglish
Article numberbts171
Pages (from-to)1549-1550
Number of pages2
JournalBioinformatics
Volume28
Issue number11
DOIs
Publication statusPublished - Jun 2012

Fingerprint

Chemical Reaction Networks
Biochemical Networks
Reaction Network
Systems Biology
Identifiability
Metabolic Networks and Pathways
Chemical reactions
Software
Network Model
Cell signaling
Metabolic Network
Signaling Pathways
Circuit theory
Modeling
Optimization
Cell

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability
  • Medicine(all)

Cite this

CRNreals : A toolbox for distinguishability and identifiability analysis of biochemical reaction networks. / Szederkényi, G.; Banga, Julio R.; Alonso, Antonio A.

In: Bioinformatics, Vol. 28, No. 11, bts171, 06.2012, p. 1549-1550.

Research output: Contribution to journalArticle

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