title: CRNreals: a toolbox for distinguishability and identifiability analysis of biochemical reaction networks.
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.
  
  
  METHODS
  The CRNreals toolbox and the associated documentation are available at http://www.iim.csic.es/~gingproc/CRNreals/. The toolbox runs under the popular MATLAB computational environment and supports several free and commercial linear programming and mixed integer linear programming solvers.
authors.affiliation: (Bio)Process Engineering Group, IIM-CSIC, Spanish National Research Council, C/Eduardo Cabello 6, Vigo, Spain. szeder@scl.sztaki.hu.
authors.forename: Gábor
authors.initials: G
authors.lastname: Szederkényi
authors.forename: Julio R
authors.initials: JR
authors.lastname: Banga
authors.forename: Antonio A
authors.initials: AA
authors.lastname: Alonso
mesh_terms: D000818:Animals; D006801:Humans; D053858:Metabolic Networks and Pathways; D015398:Signal Transduction; D012984:Software; D049490:Systems Biology / Q000379:methods*