A unified framework for estimating parameters of kinetic biological models
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Utilizing kinetic models of biological systems commonly require computational approaches to estimate parameters, posing a variety of challenges due to their highly non-linear and dynamic nature, which is further complicated by the issue of non-identifiability. We propose a novel parameter estimation framework by combining approaches for solving identifiability with a recently introduced filtering technique that can uniquely estimate parameters where conventional methods fail. This framework first conducts a thorough analysis to identify and classify the non-identifiable parameters and provides a guideline for solving them. If no feasible solution can be found, the framework instead initializes the filtering technique with informed prior to yield a unique solution.
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BAKER, Syed Murtuza, C. Hart POSKAR, Falk SCHREIBER, Björn H. JUNKER, 2015. A unified framework for estimating parameters of kinetic biological models. In: BMC Bioinformatics. 2015, 16, 104. eISSN 1471-2105. Available under: doi: 10.1186/s12859-015-0500-9BibTex
@article{Baker2015-12unifi-37681, year={2015}, doi={10.1186/s12859-015-0500-9}, title={A unified framework for estimating parameters of kinetic biological models}, volume={16}, journal={BMC Bioinformatics}, author={Baker, Syed Murtuza and Poskar, C. Hart and Schreiber, Falk and Junker, Björn H.}, note={Article Number: 104} }
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