ADGenKinetics: An Algorithmically Differentiated Library for Biochemical Networks Modeling via Simplified Kinetics Formats

Atiyah Elsheikh
Austrian Institute of Technology, Vienna, Austria

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp12076915

Ingår i: Proceedings of the 9th International MODELICA Conference; September 3-5; 2012; Munich; Germany

Linköping Electronic Conference Proceedings 76:95, s. 915-926

Visa mer +

Publicerad: 2012-11-19

ISBN: 978-91-7519-826-2

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


This work demonstrates the compact but powerful freely available Modelica library ADGenKinetics for descriptive modeling of biochemical reaction networks using simplified kinetics formats. While existing powerful works and guidelines for modeling biochemical reaction networks based on classical mechanistic kinetics already exist; in this work a first attempt of utilizing the power of Modelica constructs for providing a compact implementation of simplified kinetic formats with generalized structured formulas is presented. This gives the opportunity of realizing biochemical reaction networks using few number of reaction components; in contrast to libraries based on classical mechanistic kinetics which require hundreds of reaction components. ADGenKinetics is the first algorithmically differentiated Modelica library that is enhanced with differentiated components by which parameter sensitivities are additionally computed with minimal efforts from the user perspective.


Enzyme Kinetics; Biochemical Reaction Networks; Systems Biology; Algorithmic Differentiation


[1] H. Bisswanger. Enzyme Kinetics; Principles and Methods. WILEY-VCH Verlag; Weinheim; Germany; 2002. doi: 10.1002/3527601759.

[2] P. Droste; S. Noack; K. Noh; and W. Wiechert. Customizable visualization of multi-omics data in the context of biochemical networks. In VIZ 2009: The 2nd International Conference on Information Visualisation; Barcelona; Spain; 2009.

[3] A. Elsheikh. Modelica-based computational tools for sensitivity analysis via automatic differentiation. PhD thesis; submitted to Institute of Computer Science; RWTH Aachen University; Aachen; Germany; 2011.

[4] A. Elsheikh; S. Noack; and W. Wiechert. Sensitivity analysis of Modelica applications via automatic differentiation. In Modelica’2008: The 6th International Modelica Conference; Bielefeld; Germany; 2008.

[5] A. Elsheikh and W. Wiechert. Automatic sensitivity analysis of DAE-systems generated from equation-based modeling languages. In C. H. Bischof; H. M. Bücker; P. D. Hovland; U. Naumann; and J. Utke; editors; Advances in Automatic Differentiation; pages 235–246. Springer; 2008.

[6] A. Griewank. Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation. Number 19 in Frontiers in Appl. Math. SIAM; Philadelphia; PA; 2000.

[7] F. Hadlich; S. Noack; and W. Wiechert. Translating biochemical network models between different kinetic formats. Metabolic Engineering; 11(2):87 – 100; 2009. doi: 10.1016/j.ymben.2008.10.002.

[8] J. J. Heijnen. Approximative kinetic formats used in metabolic network modeling. Biotechnology and Bioengineering; 91(5):534–545; 2005. doi: 10.1002/bit.20558.

[9] E. Klipp; R. Herwig; A. Kowald; C. Wierling; and H. Lehrach. Systems Biology in Practice: Concepts; Implementation and Application. Wiley-VCH; 2005. doi: 10.1002/3527603603.

[10] W. Liebermeister and E. Klipp. Bringing metabolic networks to life: convenience rate law and thermodynamic constraints. Theoretical Biology and Medical Modelling; 2006.

[11] U. Naumann. The art of Differentiating Computer Programs; an Introduction to Algorithmic Differentiation. SIAM; 2012.

[12] E. L. Nilsson and P. Fritzson. A Metabolic Specialization of a General Purpose Modelica Library for Biological and Biochemical Systems. In Proceeding of the 4th International Modelica Conference; Hamburg; Germany; 2005.

[13] J. Tillack; P. Droste; N. Hackbarth; W. Wiechert; and K. Nöh. Visually-assisted modeling of kinetic metabolic networks - from Omix to Modelica and back. In MATHMOD 2012: The 7th Vienna International Conference on Mathematical Modelling; Vienna; Austria; 2012.

[14] S. A. Wahl. Methoden zur integrierten Analyse metabolischer Netzwerke unter stationären und instationären Bedingungen. PhD thesis; Research Centre Jülich; Germany; 2007.

[15] W. Wiechert; S. Noack; and A. Elsheikh. Modeling languages for biochemical network simulation: Reaction vs equation based approaches. Advances in Biochemical Engineering / Biotechnology; 2010.

[16] W. Wiechert and R. Takors. Validation of metabolic models: Concepts; tools; and problems. In H. V. Westerhoff and B. Kholodenko; editors; Metabolic Engineering in the Post Genomic Era (Horizon Bioscience). Horizon Scientific Press; 2004.

Citeringar i Crossref