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Multistep generalized transformation method applied to solving equations of discrete and continuous time-fractional enzyme kinetics
dc.creator | Vosika, Zoran B. | |
dc.creator | Mitić, Vojislav V. | |
dc.creator | Vasić, Aleksandar | |
dc.creator | Lazović, Goran | |
dc.creator | Matija, Lidija | |
dc.creator | Kocić, Ljubiša | |
dc.date.accessioned | 2018-04-11T10:12:12Z | |
dc.date.available | 2018-04-11T10:12:12Z | |
dc.date.issued | 2017 | |
dc.identifier.issn | 1007-5704 | |
dc.identifier.uri | https://dais.sanu.ac.rs/123456789/2358 | |
dc.description.abstract | In this paper, Caputo based Michaelis–Menten kinetic model based on Time Scale Calculus (TSC) is proposed. The main reason for its consideration is a study of tumor cells population growth dynamics. In the particular case discrete-continuous time kinetics, Michaelis–Menten model is numerically treated, using a new algorithm proposed by authors, called multistep generalized difference transformation method (MSGDETM). In addition numerical simulations are performed and is shown that it represents the upgrade of the multi-step variant of generalized differential transformation method (MSGDTM). A possible conditions for its further development are discussed and possible experimental verification is described. | en |
dc.format | 44 (2017) 373-389 | |
dc.language | en | |
dc.publisher | Elsevier | |
dc.rights | restrictedAccess | |
dc.source | Communications in Nonlinear Science and Numerical Simulation | en |
dc.subject | kinetics | |
dc.subject | discrete fractional calculus | |
dc.subject | nonlinear systems | |
dc.title | Multistep generalized transformation method applied to solving equations of discrete and continuous time-fractional enzyme kinetics | en |
dc.type | article | |
dc.rights.license | ARR | |
dcterms.abstract | Митић, Војислав В.; Восика, З.; Васић, A.; Лазовић, Г.; Матија, Лидија; Коцић, Љубиша М.; | |
dc.citation.spage | 373 | |
dc.citation.epage | 389 | |
dc.citation.volume | 44 | |
dc.identifier.wos | 000386744400031 | |
dc.identifier.doi | 10.1016/j.cnsns.2016.08.024 | |
dc.identifier.scopus | 2-s2.0-84986550432 | |
dc.type.version | publishedVersion | |
dc.identifier.rcub | https://hdl.handle.net/21.15107/rcub_dais_2358 |