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Systems biology: parameter estimation for biochemical models
Author(s) -
Ashyraliyev Maksat,
FomekongNanfack Yves,
Kaandorp Jaap A.,
Blom Joke G.
Publication year - 2009
Publication title -
the febs journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 204
eISSN - 1742-4658
pISSN - 1742-464X
DOI - 10.1111/j.1742-4658.2008.06844.x
Subject(s) - identifiability , estimation theory , parameter space , computer science , experimental data , mathematical model , estimation , biological system , machine learning , mathematics , algorithm , biology , statistics , engineering , systems engineering
Mathematical models of biological processes have various applications: to assist in understanding the functioning of a system, to simulate experiments before actually performing them, to study situations that cannot be dealt with experimentally, etc. Some parameters in the model can be directly obtained from experiments or from the literature. Others have to be inferred by comparing model results to experiments. In this minireview, we discuss the identifiability of models, both intrinsic to the model and taking into account the available data. Furthermore, we give an overview of the most frequently used approaches to search the parameter space.