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A parameter estimation approach for non-linear systems biology models using spline approximation

Published: 02 August 2010 Publication History

Abstract

Mathematical models for revealing the dynamics and interactions properties of biological systems play an important role in computational systems biology. The inference of model parameter values from time-course data can be considered as a "reverse engineering" process and still one of the most challenging tasks. It is worth to develop parameter estimation methods which are robust against noise, efficient in computation and flexible enough to meet different constraints. Parameter estimation method of combining spline theory with Nonlinear Programming (NLP) is developed. The method removes the need for ODE solver during the identification process. Our analysis shows that the augmented cost function surface used in the proposed method is smoother than the original one; which can ease the optima searching process and hence enhance the robustness and speed. Moreover, the core of our algorithms is NLP based, which is very flexible and consequently additional constraints can be added/removed easily. Our results confirm that the proposed method is both efficient and robust.

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  • (2014)A parameter estimation method for biological systems modelled by ODE/DDE models using spline approximation and differential evolution algorithmIEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)10.1109/TCBB.2014.232236011:6(1066-1076)Online publication date: 1-Nov-2014

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cover image ACM Conferences
BCB '10: Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
August 2010
705 pages
ISBN:9781450304382
DOI:10.1145/1854776
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 02 August 2010

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Author Tags

  1. nonlinear programming
  2. parameter estimation
  3. spline

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View all
  • (2019)Modelling for Dynamic Growth of User Population of Products and Services2019 IEEE 17th International Conference on Industrial Informatics (INDIN)10.1109/INDIN41052.2019.8972127(1478-1482)Online publication date: Jul-2019
  • (2014)A parameter estimation method for biological systems modelled by ODE/DDE models using spline approximation and differential evolution algorithmIEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)10.1109/TCBB.2014.232236011:6(1066-1076)Online publication date: 1-Nov-2014

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