Initial state perturbations as a validation method for data-driven fuzzy models of cellular networks
Magdevska, Lidija (Author), Mraz, Miha (Author), Zimic, Nikolaj (Author), Moškon, Miha (Author)

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Background: Data-driven methods that automatically learn relations between attributes from given data are a popular tool for building mathematical models in computational biology. Since measurements are prone to errors, approaches dealing with uncertain data are especially suitable for this task. Fuzzy models are one such approach, but they contain a large amount of parameters and are thus susceptible to over-fitting. Validation methods that help detect over-fitting are therefore needed to eliminate inaccurate models. Results: We propose a method to enlarge the validation datasets on which a fuzzy dynamic model of a cellular network can be tested. We apply our method to two data-driven dynamic models of the MAPK signalling pathway and two models of the mammalian circadian clock. We show that random initial state perturbations can drastically increase the mean error of predictions of an inaccurate computational model, while keeping errors of predictions of accurate models small. Conclusions: With the improvement of validation methods, fuzzy models are becoming more accurate and are thus likely to gain new applications. This field of research is promising not only because fuzzy models can cope with uncertainty, but also because their run time is short compared to conventional modelling methods that are nowadays used in systems biology.

Keywords:fuzzy logic, modelling and simulation, data-driven modelling, cellular networks, computational biology, model validation, dynamic modelling, MAPK signalling pathway, circadian clock
Work type:Article (dk_c)
Tipology:1.01 - Original Scientific Article
Organization:FRI - Faculty of computer and information science
FMF - Faculty of Mathematics and Physics
Number of pages:Str. 1-7
Numbering:Vol. 19, art. 333
ISSN on article:1471-2105
DOI:10.1186/s12859-018-2366-0 This link opens in a new window
COBISS.SI-ID:1537917379 This link opens in a new window
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Record is a part of a journal

Title:BMC bioinformatics
Publisher:Springer Nature
COBISS.SI-ID:2433556 This link opens in a new window

Document is financed by a project

Funder:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Project no.:P2-0359
Name:Vseprisotno računalništvo

Funder:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Project no.:J1-9176
Name:HolesteROR pri presnovnih boleznih jeter

Funder:Drugi - Drug financer ali več financerjev
Funding Programme:Scholarship of the City of Ljubljana
Project no.:


License:CC BY 4.0, Creative Commons Attribution 4.0 International
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:25.03.2021

Secondary language

Keywords:mehka logika, modeliranje in simulacija, podatkovno vodeno modeliranje, celična omrežja, računska biologija

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