Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Evans, N. D.; Moyse, H. A. J.; Lowe, David Philip; Briggs, D.; Higgins, R.; Mitchell, Daniel Anthony; Zehnder, Daniel; Chappell, M. J. (Michael J.) (2013)
Publisher: Pergamon
Languages: English
Types: Article
Subjects: QC, QD
Binding affinities are useful measures of target interaction and have an important role in understanding biochemical reactions that involve binding mechanisms. Surface plasmon resonance (SPR) provides convenient real-time measurement of the reaction that enables subsequent estimation of the reaction constants necessary to determine binding affinity. Three models are\ud considered for application to SPR experiments—the well mixed Langmuir model and two models that represent the binding reaction in the presence of transport effects. One of these models, the effective rate constant approximation, can be derived from the other by applying a quasi-steady state assumption. Uniqueness of the reaction constants with respect to SPR measurements\ud is considered via a structural identifiability analysis. It is shown that the models are structurally unidentifiable unless the sample concentration is known. The models are also considered for analytes with heterogeneity in the binding kinetics. This heterogeneity further confounds the identifiability of key parameters necessary for reliable estimation of the binding affinity
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • D.G. Myszka, X. He, M. Dembo, T.A. Morton, and B. Goldstein. Extending the range of rate constants available from BIACORE: Interpreting mass transport-influenced binding data. Biophys. J., 75: 583-594, 1998.
    • D.A. Edwards, B. Goldstein, and D.S. Cohen. Transport effects on surface-volume biological reactions:. J. Math. Biol., 39:533-561, 1999.
    • D.A. Edwards. The effect of a receptor layer on the measurement of rate constants. B. Math. Biol., 63: 301-327, 2001.
    • I. Chaiken, S. Rose´e, and R. Karlsson. Analysis of macromolecularinteractions using immobilzed ligands. Anal. Biochem., 201:197-210, 1992.
    • R. Bellman and K.J. A˚stro¨m. On structural identifiability. Mathematical Biosciences, 7:329-339, 1970.
    • J.A. Jacquez. Compartmental Analysis in Biology and Medicine. BioMedware, Ann Arbor, MI, 1996.
    • K.R. Godfrey and J.J. DiStefano III. Identifiability of model parameters. In E. Walter, editor, Identifiability of Parametric Models, chapter 1, pages 1-20. Pergamon Press, 1987.
    • E. Walter. Identifiability of State Space Models. SpringerVerlag, 1982.
    • H. Pohjanpalo. System identifiability based on the power series expansion of the solution. Math. Biosci., 41: 21-33, 1978.
    • G. Margaria, E. Riccomagno, M.J. Chappell, and H.P. Wynn. Differential algebra methods for the study of the structural identifiability of rational polynomial state-space models in the biosciences. Mathematical Biosciences, 174:1-26, 2001.
    • N.D. Evans, M.J. Chapman, M.J. Chappell, and K.R. Godfrey. Identifiability of uncontrolled nonlinear rational systems. Automatica, 38:1799-1805, 2002.
    • L. Ljung and T. Glad. On global identifiability for arbitrary model parametrizations. Automatica, 30:265- 276, 1994.
    • M.P. Saccomani, S. Audoly, and L. D'Angio`. Parameter identifiability of nonlinear systems: the role of initial conditions. Automatica, 39:619-632, 2003.
    • J. Nˇemcova´. Structural identifiability of polynomial and rational systems. Math. Biosci., 223:83-96, 2010.
    • L. Denis-Vidal, G. Joly-Blanchard, and C. Noiret. Some effective approachesto check identifiability of uncontrolled nonlinear rational systems. Math. Comput. Simulat., 57:35-44, 2001.
    • A. Isidori. Nonlinear Control Systems. Springer, 1995.
    • F. Ollivier. Le probl´eme de lidentifiabilit´e structurelle globale: ´etude th´eorique, m´ethodes effectives et bornes de complexit´e. Th`ese de doctorat en science, Ecole polytechnique, Paris, France, 1990.
    • S.T. Glad and L. Ljung. Model structure identifiability and persistence of excitation. In Proceedings of the 29th IEEE Conference on Decision and Control, pages 3236-3240, 1990.
    • S. Audoly, G. Bellu, L. D'Angio`, M.P. Saccomani, and C. Cobelli. Global identifiability of nonlinear models of biological systems. IEEE Transactions on Biomedical Engineering, 48:55-65, 2001.
    • S.T. Glad. Nonlinear input output relations and identifiability. In Proceedings of the 31st Conference on Decision and Control, 1992.
    • S.T. Glad. Input output representations from characteristic sets. In Proceedlngs of the 30th Conference on Decision and Control, pages 726-730, Brighton, England, December 1991.
    • M.P. Saccomani, S. Audoly, G. Bellu, and L. D'Angio`. A new differential algebra algorithm to test identifiability of nonlinear systems with given initial conditions. In Proceedings of the 40th IEEE Conference on Decision and Control, 2001.
    • D. Bearup, N.D. Evans, and M.J. Chappell. The inputoutput relationship approach to structural identifiability analysis. Submitted to Computer Methods and Programs in Biomedicine, 2011.
    • K. Forsman. Constructive Commutative Algebra in Nonlinear Control Theory. PhD thesis, Linko¨ping Institute of Technology, 1991. Number 261.
    • T. Andersson. Concepts and Algorithms for Non-linear System Identifiability. PhD thesis, Linko¨ping University, 1994. Number 448.
    • R. Hermann and A.J. Krener. Nonlinear controllability and observability. IEEE Transactions on Automatic Control, AC-22:728-740, 1977.
    • S.T. Glad. Differential algebraic modelling of nonlinear systems. In MA Kaashoek, JH van Schuppen, and ACM Ran, editors, Realization and Modelling in System Theory, Proceedings of the International Symposium MTNS-89, volume I, pages 97-105. Birkh¨auser, 1990.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article