Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy sets

Quantitative demonstrating of organic frameworks has turned into an essential computational methodology in the configuration of novel and investigation of existing natural frameworks. Be that as it may, active information that portrays the framework's elements should be known keeping in mind th...

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Main Author: Raed I. Hamed
Format: Article
Language:English
Published: Elsevier 2018-01-01
Series:Journal of King Saud University: Science
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1018364716307819
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spelling doaj-649db9a7fcbb4599be4308d56067267c2020-11-24T22:26:06ZengElsevierJournal of King Saud University: Science1018-36472018-01-0130111211910.1016/j.jksus.2017.01.005Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy setsRaed I. HamedQuantitative demonstrating of organic frameworks has turned into an essential computational methodology in the configuration of novel and investigation of existing natural frameworks. Be that as it may, active information that portrays the framework's elements should be known keeping in mind the end goal to get pertinent results with the routine displaying strategies. This information is frequently robust or even difficult to get. Here, we exhibit a model of quantitative fuzzy rational demonstrating approach that can adapt to obscure motor information and hence deliver applicable results despite the fact that dynamic information is fragmented or just dubiously characterized. Besides, the methodology can be utilized as a part of the blend with the current cutting edge quantitative demonstrating strategies just in specific parts of the framework, i.e., where the data are absent. The contextual analysis of the methodology suggested in this paper is performed on the model of nine-quality genes. We propose a kind of FPN model in light of fuzzy sets to manage the quantitative modeling of biological systems. The tests of our model appear that the model is practical and entirely powerful for information impersonation and thinking of fuzzy expert frameworks.http://www.sciencedirect.com/science/article/pii/S1018364716307819FPNsFuzzy setsUncertain dataGRNsQuantitative modeling
collection DOAJ
language English
format Article
sources DOAJ
author Raed I. Hamed
spellingShingle Raed I. Hamed
Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy sets
Journal of King Saud University: Science
FPNs
Fuzzy sets
Uncertain data
GRNs
Quantitative modeling
author_facet Raed I. Hamed
author_sort Raed I. Hamed
title Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy sets
title_short Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy sets
title_full Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy sets
title_fullStr Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy sets
title_full_unstemmed Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy sets
title_sort quantitative modeling of gene networks of biological systems using fuzzy petri nets and fuzzy sets
publisher Elsevier
series Journal of King Saud University: Science
issn 1018-3647
publishDate 2018-01-01
description Quantitative demonstrating of organic frameworks has turned into an essential computational methodology in the configuration of novel and investigation of existing natural frameworks. Be that as it may, active information that portrays the framework's elements should be known keeping in mind the end goal to get pertinent results with the routine displaying strategies. This information is frequently robust or even difficult to get. Here, we exhibit a model of quantitative fuzzy rational demonstrating approach that can adapt to obscure motor information and hence deliver applicable results despite the fact that dynamic information is fragmented or just dubiously characterized. Besides, the methodology can be utilized as a part of the blend with the current cutting edge quantitative demonstrating strategies just in specific parts of the framework, i.e., where the data are absent. The contextual analysis of the methodology suggested in this paper is performed on the model of nine-quality genes. We propose a kind of FPN model in light of fuzzy sets to manage the quantitative modeling of biological systems. The tests of our model appear that the model is practical and entirely powerful for information impersonation and thinking of fuzzy expert frameworks.
topic FPNs
Fuzzy sets
Uncertain data
GRNs
Quantitative modeling
url http://www.sciencedirect.com/science/article/pii/S1018364716307819
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