CRNreals: a toolbox for distinguishability and identifiability analysis of biochemical reaction networks. 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.
Keywords for this software
References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
- Craciun, Gheorghe; Jin, Jiaxin; Yu, Polly Y.: Single-target networks (2022)
- Craciun, Gheorghe; Jin, Jiaxin; Yu, Polly Y.: Uniqueness of weakly reversible and deficiency zero realizations of dynamical systems (2021)
- Johnston, Matthew D.: A linear programming approach to dynamical equivalence, linear conjugacy, and the deficiency one theorem (2016)
- Lipták, György; Szederkényi, Gábor; Hangos, Katalin M.: Computing zero deficiency realizations of kinetic systems (2015)
- Rudan, János; Szederkényi, Gábor; Hangos, Katalin M.; Péni, Tamás: Polynomial time algorithms to determine weakly reversible realizations of chemical reaction networks (2014)
Further publications can be found at: http://gingproc.iim.csic.es/~gingproc/CRNreals/pubs.html