Type of Publication: | Journal article |
Publication status: | Published |
URI (citable link): | http://nbn-resolving.de/urn:nbn:de:bsz:352-0-395174 |
Author: | Baker, Syed Murtuza; Poskar, C. Hart; Schreiber, Falk; Junker, Björn H. |
Year of publication: | 2015 |
Published in: | BMC Bioinformatics ; 16 (2015). - 104. - eISSN 1471-2105 |
Pubmed ID: | 25886743 |
DOI (citable link): | https://dx.doi.org/10.1186/s12859-015-0500-9 |
Summary: |
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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Subject (DDC): | 004 Computer Science |
Link to License: | In Copyright |
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. 16, 104. eISSN 1471-2105. Available under: doi: 10.1186/s12859-015-0500-9
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