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

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URLURL - Izvorni URL, za dostop obiščite https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2366-0 Povezava se odpre v novem oknu

Izvleček
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.

Jezik:Angleški jezik
Ključne besede:fuzzy logic, modelling and simulation, data-driven modelling, cellular networks, computational biology, model validation, dynamic modelling, MAPK signalling pathway, circadian clock
Vrsta gradiva:Članek v reviji (dk_c)
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FRI - Fakulteta za računalništvo in informatiko
FMF - Fakulteta za matematiko in fiziko
Leto izida:2018
Status objave pri reviji:Objavljeno
Verzija članka:Založnikova različica članka
Št. strani:7 str.
Številčenje:Vol. 19, art. 333
PID:20.500.12556/RUL-125563 Povezava se odpre v novem oknu
UDK:004.94:57
ISSN pri članku:1471-2105
DOI:10.1186/s12859-018-2366-0 Povezava se odpre v novem oknu
COBISS.SI-ID:1537917379 Povezava se odpre v novem oknu
Datum objave v RUL:25.03.2021
Število ogledov:431
Število prenosov:187
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
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Gradivo je del revije

Naslov:BMC bioinformatics
Založnik:Springer Nature
ISSN:1471-2105
COBISS.SI-ID:2433556 Povezava se odpre v novem oknu

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:25.03.2021

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:mehka logika, modeliranje in simulacija, podatkovno vodeno modeliranje, celična omrežja, računska biologija

Projekti

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:P2-0359
Naslov:Vseprisotno računalništvo

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:J1-9176
Naslov:HolesteROR pri presnovnih boleznih jeter

Financer:Drugi - Drug financer ali več financerjev
Program financ.:Scholarship of the City of Ljubljana

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