<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">vavilov</journal-id><journal-title-group><journal-title xml:lang="ru">Вавиловский журнал генетики и селекции</journal-title><trans-title-group xml:lang="en"><trans-title>Vavilov Journal of Genetics and Breeding</trans-title></trans-title-group></journal-title-group><issn pub-type="epub">2500-3259</issn><publisher><publisher-name>Institute of Cytology and Genetics of Siberian Branch of the RAS</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18699/VJ18.341</article-id><article-id custom-type="elpub" pub-id-type="custom">vavilov-1374</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>МОЛЕКУЛЯРНЫЕ МАРКЕРЫ В ГЕНЕТИКЕ И СЕЛЕКЦИИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>BIOINFORMATICS AND SYSTEM BIOLOGY</subject></subj-group></article-categories><title-group><article-title>ОБ ЭКВИВАЛЕНТНОСТИ ИСПОЛЬЗОВАНИЯ ЗАПАЗДЫВАЮЩИХ АРГУМЕНТОВ И УРАВНЕНИЙ ПЕРЕНОСА ПРИ МОДЕЛИРОВАНИИ ДИНАМИЧЕСКИХ СИСТЕМ</article-title><trans-title-group xml:lang="en"><trans-title>ON THE EQUIVALENCE OF DELAYED ARGUMENTS AND TRANSFER EQUATIONS FOR MODELING DYNAMIC SYSTEMS</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Лихошвай</surname><given-names>В. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Likhoshvai</surname><given-names>V. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Новосибирск</p></bio><bio xml:lang="en"><p>Novosibirsk</p></bio><email xlink:type="simple">likho@bionet.nsc.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Хлебодарова</surname><given-names>Т. М.</given-names></name><name name-style="western" xml:lang="en"><surname>Khlebodarova</surname><given-names>T. M.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Новосибирск</p></bio><bio xml:lang="en"><p>Novosibirsk</p></bio><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук<country>Россия</country></aff><aff xml:lang="en">Institute of Cytology and Genetics SB RAS<country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2018</year></pub-date><pub-date pub-type="epub"><day>22</day><month>03</month><year>2018</year></pub-date><volume>22</volume><issue>1</issue><fpage>141</fpage><lpage>144</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Лихошвай В.А., Хлебодарова Т.М., 2018</copyright-statement><copyright-year>2018</copyright-year><copyright-holder xml:lang="ru">Лихошвай В.А., Хлебодарова Т.М.</copyright-holder><copyright-holder xml:lang="en">Likhoshvai V.A., Khlebodarova T.M.</copyright-holder><license license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://vavilov.elpub.ru/jour/article/view/1374">https://vavilov.elpub.ru/jour/article/view/1374</self-uri><abstract><p>Разработка и совершенствование методов математического моделирования биологических систем – актуальное направление математической биологии. В статье рассмотрена система общего вида дифференциальных уравнений первого порядка с постоянными запаздывающими аргументами, широко используемая в качестве математического аппарата для описания и анализа динамики функционирования биологических систем практически на всех уровнях их организации. К основной особенности данного класса моделей относится то, что некоторые процессы, явно протекающие в биосистемах (например, стадии элонгации синтеза ДНК, РНК, белков), описываются в скрытой форме и в модели проявлены только через запаздывающие аргументы. В настоящей работе мы предлагаем алгоритм переписывания систем с постоянными запаздывающими аргументами в эквивалентной форме, представляющей систему дифференциальных уравнений в частных производных с уравнениями переноса. Алгоритм переписывания универсален, поскольку не накладывает каких-либо специальных условий на вид правых частей систем с запаздывающими аргументами. Предложенный алгоритм является многовариантным, т.е. позволяет по одной системе дифференциальных уравнений с запаздывающими аргументами выписывать несколько специальных систем дифференциальных уравнений в частных производных, которые на множестве решений эквивалентны исходной системе с запаздывающим аргументом. Полученные результаты демонстрируют, что постоянные запаздывающие аргументы и уравнения переноса с постоянными коэффициентами являются равноценными математическими аппаратами для описания всех типов динамических процессов переноса энергии и/или вещества в биологических, химических и физических системах. В то же время системы уравнений с частными производными позволяют описывать в явном виде, в форме уравнений переноса, те процессы, которые скрыты в запаздывающем аргументе. Это весьма важное свойство, если речь идет о моделировании молекулярно-генетических систем, в которых процессы синтеза ДНК, РНК и белков протекают с неравномерной скоростью и в определенных задачах требуют учета, что легко можно сделать в моделях, построенных с использованием математического аппарата частных производных.</p></abstract><trans-abstract xml:lang="en"><p>Development and improvement of mathematical methods used in modeling biological systems represents a topical issue of mathematical biology. In this paper, we considered a general form of a system of first-order delayed differential equations, traditionally used for describing the function of biological systems of different hierarchical levels. The main feature of this class of models is that some inherent processes (for example, elongation of DNA, RNA, and protein synthesis) are described in a subtle form and can be explicitly specified only through delayed arguments. In this paper, we propose an algorithm for rewriting systems with constant delayed arguments in an equivalent form that represents a system of partial differential equations with transfer equations. The algorithm is universal, since it does not impose any special conditions on the form of the right-hand parts of systems with delayed arguments. The proposed method is a multivariant algorithm. That is, based on one system of differential equations with delayed arguments, the algorithm allows writing out a number of special systems of partial differential equations, which are equivalent to the original system with delayed argument in the entire solution set. The results obtained indicate that delayed arguments and transfer equations are equivalent mathematical tools for describing all types of dynamic processes of energy and/or matter transfer in biological, chemical, and physical systems, indicating a deep-level similarity between properties of dynamic systems, regardless of their origin. At the same time, those processes that are subtle when retarded argument is used can be explicitly described in the form of transfer equations using systems of partial differential equations. This property is extremely important for the modeling of molecular genetic systems in which processes of DNA, RNA, and protein synthesis proceed at variable rates and need to be considered in certain problems, what can easily be done in models constructed using the mathematical tool of partial derivatives.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>обыкновенные дифференциальные уравнения</kwd><kwd>запаздывающий аргумент</kwd><kwd>уравнения в частных производных</kwd><kwd>уравнения переноса</kwd><kwd>моделирование</kwd><kwd>динамические системы</kwd><kwd>математическая биология</kwd></kwd-group><kwd-group xml:lang="en"><kwd>ordinary differential equations</kwd><kwd>delayed argument</kwd><kwd>partial differential equations</kwd><kwd>transfer equations</kwd><kwd>modeling</kwd><kwd>dynamical systems</kwd><kwd>mathematical biology</kwd></kwd-group><funding-group xml:lang="en"><funding-statement>State Budgeted Project 0324-2016-0008 and the Russian Foundation for Basic Research, project 16-01-00237a</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Bhat D., Gopalakrishnan M. Transport of organelles by elastically coupled motor proteins. Eur. Phys. J. E. 2016;39(7):71. DOI 10.1140/epje/i2016-16071-0.</mixed-citation><mixed-citation xml:lang="en">Bhat D., Gopalakrishnan M. Transport of organelles by elastically coupled motor proteins. Eur. Phys. J. E. 2016;39(7):71. DOI 10.1140/epje/i2016-16071-0.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Bocharov G.A., Rihan F.A. Numerical modelling in biosciences using delay differential equations. J. Comput. Appl. Math. 2000;125(1-2): 183-199.</mixed-citation><mixed-citation xml:lang="en">Bocharov G.A., Rihan F.A. Numerical modelling in biosciences using delay differential equations. J. Comput. Appl. Math. 2000;125(1-2): 183-199.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Busenberg S., Tang B. Mathematical models of the early embryonic cell cycle: the role of MPF activation and cyclin degradation. J. Math. Biol. 1994;32:573-596.</mixed-citation><mixed-citation xml:lang="en">Busenberg S., Tang B. Mathematical models of the early embryonic cell cycle: the role of MPF activation and cyclin degradation. J. Math. Biol. 1994;32:573-596.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Dayananda P.W., Kemper J.T., Shvartsman M.M. A stochastic model for prostate-specific antigen levels. Math. Biosci. 2004;190(2): 113-126.</mixed-citation><mixed-citation xml:lang="en">Dayananda P.W., Kemper J.T., Shvartsman M.M. A stochastic model for prostate-specific antigen levels. Math. Biosci. 2004;190(2): 113-126.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Demidenko G.V., Likhoshvai V.A. On differential equations with retarded argument. Siberian Mathematical Journal. 2005;46(3):417-430.</mixed-citation><mixed-citation xml:lang="en">Demidenko G.V., Likhoshvai V.A. On differential equations with retarded argument. Siberian Mathematical Journal. 2005;46(3):417-430.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">El’sgol’ts L.E., Norkin S.B. Vvedenie v teoriyu differentsial'nykh uravneniy s otklonyayushchimsya argumentom [Introduction to the Theory of Differential Equations with Deviating Argument]. Moscow: Nauka Publ., 1971;296. (in Russian)</mixed-citation><mixed-citation xml:lang="en">El’sgol’ts L.E., Norkin S.B. Vvedenie v teoriyu differentsial'nykh uravneniy s otklonyayushchimsya argumentom [Introduction to the Theory of Differential Equations with Deviating Argument]. Moscow: Nauka Publ., 1971;296. (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Gelens L., Huang K.C., Ferrell J.E., Jr. How does the Xenopus laevis embryonic cell cycle avoid spatial chaos? Cell Rep. 2015;12(5): 892-900. DOI 10.1016/j.celrep.2015.06.070.</mixed-citation><mixed-citation xml:lang="en">Gelens L., Huang K.C., Ferrell J.E., Jr. How does the Xenopus laevis embryonic cell cycle avoid spatial chaos? Cell Rep. 2015;12(5): 892-900. DOI 10.1016/j.celrep.2015.06.070.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Gérard C., Goldbeter A. Entrainment of the mammalian cell cycle by the circadian clock: modeling two coupled cellular rhythms. PLoS Comput. Biol. 2012;8(5):e1002516. DOI 10.1371/journal.pcbi.1002516.</mixed-citation><mixed-citation xml:lang="en">Gérard C., Goldbeter A. Entrainment of the mammalian cell cycle by the circadian clock: modeling two coupled cellular rhythms. PLoS Comput. Biol. 2012;8(5):e1002516. DOI 10.1371/journal.pcbi.1002516.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Harrison L.M., David O., Friston K.J. Stochastic models of neuronal dynamics. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 2005; 360(1457):1075-1091.</mixed-citation><mixed-citation xml:lang="en">Harrison L.M., David O., Friston K.J. Stochastic models of neuronal dynamics. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 2005; 360(1457):1075-1091.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Khlebodarova T.M., Kogai V.V., Fadeev S.I., Likhoshvai V.A. Chaos and hyperchaos in simple gene network with negative feedback and time delays. J. Bioinform. Comput. Biol. 2017;15(2):1650042. DOI 10.1142/S0219720016500426.</mixed-citation><mixed-citation xml:lang="en">Khlebodarova T.M., Kogai V.V., Fadeev S.I., Likhoshvai V.A. Chaos and hyperchaos in simple gene network with negative feedback and time delays. J. Bioinform. Comput. Biol. 2017;15(2):1650042. DOI 10.1142/S0219720016500426.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Kogai V.V., Khlebodarova T.M., Fadeev S.I., Likhoshvai V.A. Complex dynamics in alternative mRNA splicing systems: mathematical model. Vychislitelnye tekhnologii = Computational Technologies. 2015;20(1):38-52. (in Russian)</mixed-citation><mixed-citation xml:lang="en">Kogai V.V., Khlebodarova T.M., Fadeev S.I., Likhoshvai V.A. Complex dynamics in alternative mRNA splicing systems: mathematical model. Vychislitelnye tekhnologii = Computational Technologies. 2015;20(1):38-52. (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Kogai V.V., Likhoshvai V.A., Fadeev S.I., Khlebodarova T.M. Multiple scenarios of transition to chaos in the alternative splicing model. Int. J. Bifurcat. Chaos. 2017;27(2):1730006. DOI 10.1142/S0218127417300063.</mixed-citation><mixed-citation xml:lang="en">Kogai V.V., Likhoshvai V.A., Fadeev S.I., Khlebodarova T.M. Multiple scenarios of transition to chaos in the alternative splicing model. Int. J. Bifurcat. Chaos. 2017;27(2):1730006. DOI 10.1142/S0218127417300063.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Likhoshvai V.A., Fadeev S.I., Demidenko G.V., Matushkin Yu.G. Modeling of multistage synthesis of a substance without branching by an equation with a retarded argument. Sibirskiy zhurnal industrialnoy matematiki = Siberian Journal of Industrial Mathematics. 2004; 7(1):73-94. (in Russian)</mixed-citation><mixed-citation xml:lang="en">Likhoshvai V.A., Fadeev S.I., Demidenko G.V., Matushkin Yu.G. Modeling of multistage synthesis of a substance without branching by an equation with a retarded argument. Sibirskiy zhurnal industrialnoy matematiki = Siberian Journal of Industrial Mathematics. 2004; 7(1):73-94. (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Likhoshvai V.A., Fadeev S.I., Kogai V.V., Khlebodarova T.M. On the chaos in gene networks. J. Bioinform. Comput. Biol. 2013;11(1): 1340009. DOI 10.1142/S021972001340009.</mixed-citation><mixed-citation xml:lang="en">Likhoshvai V.A., Fadeev S.I., Kogai V.V., Khlebodarova T.M. On the chaos in gene networks. J. Bioinform. Comput. Biol. 2013;11(1): 1340009. DOI 10.1142/S021972001340009.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Likhoshvai V.A., Kogai V.V., Fadeev S.I., Khlebodarova T.M. Alternative splicing can lead to chaos. J. Bioinform. Comput. Biol. 2015; 13:1540003. DOI 10.1142/S021972001540003X.</mixed-citation><mixed-citation xml:lang="en">Likhoshvai V.A., Kogai V.V., Fadeev S.I., Khlebodarova T.M. Alternative splicing can lead to chaos. J. Bioinform. Comput. Biol. 2015; 13:1540003. DOI 10.1142/S021972001540003X.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Likhoshvai V.A., Kogai V.V., Fadeev S.I., Khlebodarova T.M. Chaos and hyperchaos in a model of ribosome autocatalytic synthesis. Sci. Rep. 2016;6:38870. DOI 10.1038/srep38870.</mixed-citation><mixed-citation xml:lang="en">Likhoshvai V.A., Kogai V.V., Fadeev S.I., Khlebodarova T.M. Chaos and hyperchaos in a model of ribosome autocatalytic synthesis. Sci. Rep. 2016;6:38870. DOI 10.1038/srep38870.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Likhoshvai V.A., Matushkin Yu.G., Fadeev S.I. Problems of the theory of gene networks functioning. Sibirskiy zhurnal industrialnoy matematiki = Siberian Journal of Industrial Mathematics. 2003;6:64-80. (in Russian)</mixed-citation><mixed-citation xml:lang="en">Likhoshvai V.A., Matushkin Yu.G., Fadeev S.I. Problems of the theory of gene networks functioning. Sibirskiy zhurnal industrialnoy matematiki = Siberian Journal of Industrial Mathematics. 2003;6:64-80. (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Lu H., Song H., Zhu H. A series of population models for Hyphantria cunea with delay and seasonality. Math. Biosci. 2017;292:57-66.DOI 10.1016/j.mbs.2017.07.010.</mixed-citation><mixed-citation xml:lang="en">Lu H., Song H., Zhu H. A series of population models for Hyphantria cunea with delay and seasonality. Math. Biosci. 2017;292:57-66.DOI 10.1016/j.mbs.2017.07.010.</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">McIsaac R.S., Huang K.C., Sengupta A., Wingreen N.S. Does the potential for chaos constrain the embryonic cell-cycle oscillator? PLoS Comput. Biol. 2011;7:e1002109.</mixed-citation><mixed-citation xml:lang="en">McIsaac R.S., Huang K.C., Sengupta A., Wingreen N.S. Does the potential for chaos constrain the embryonic cell-cycle oscillator? PLoS Comput. Biol. 2011;7:e1002109.</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Monk N.A.M. Oscillatory expression of Hes1, p53, and NF-κB driven by transcriptional time delays. Curr. Biol. 2003;13(16):1409-1413.</mixed-citation><mixed-citation xml:lang="en">Monk N.A.M. Oscillatory expression of Hes1, p53, and NF-κB driven by transcriptional time delays. Curr. Biol. 2003;13(16):1409-1413.</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Myshkis A.D. General theory of delay differential equations. Uspekhi matematicheskikh nauk = Advances in Mathematical Sciences. 1949;4(5(33)):99-141. (in Russian)</mixed-citation><mixed-citation xml:lang="en">Myshkis A.D. General theory of delay differential equations. Uspekhi matematicheskikh nauk = Advances in Mathematical Sciences. 1949;4(5(33)):99-141. (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Nelson P.W., Murray J.D., Perelson A.S. A model of HIV-1 pathogenesis that includes an intracellular delay. Math. Biosci. 2000;163(2): 201-215.</mixed-citation><mixed-citation xml:lang="en">Nelson P.W., Murray J.D., Perelson A.S. A model of HIV-1 pathogenesis that includes an intracellular delay. Math. Biosci. 2000;163(2): 201-215.</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Nelson P.W., Perelson A.S. Mathematical analysis of delay differential equation models of HIV-1 infection. Math. Biosci. 2002;179:73-94.</mixed-citation><mixed-citation xml:lang="en">Nelson P.W., Perelson A.S. Mathematical analysis of delay differential equation models of HIV-1 infection. Math. Biosci. 2002;179:73-94.</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Risken H. The Fokker–Planck equation. Berlin: Springer, 1996.</mixed-citation><mixed-citation xml:lang="en">Risken H. The Fokker–Planck equation. Berlin: Springer, 1996.</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Romond P.C., Rustici M., Gonze D., Goldbeter A. Alternating oscillations and chaos in a model of two coupled biochemical oscillators driving successive phases of the cell cycle. Ann. NY Acad. Sci. 1999;879:180-193.</mixed-citation><mixed-citation xml:lang="en">Romond P.C., Rustici M., Gonze D., Goldbeter A. Alternating oscillations and chaos in a model of two coupled biochemical oscillators driving successive phases of the cell cycle. Ann. NY Acad. Sci. 1999;879:180-193.</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Salapaka S., Rowchowdhury S., Salapaka M. Modeling and role of feedback controlled stochastic ratchets in cellular transport. Proc. of the 51st IEEE Conf. on Decision and Control. 2012;6426263:374-379.</mixed-citation><mixed-citation xml:lang="en">Salapaka S., Rowchowdhury S., Salapaka M. Modeling and role of feedback controlled stochastic ratchets in cellular transport. Proc. of the 51st IEEE Conf. on Decision and Control. 2012;6426263:374-379.</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Srividhya J., Gopinathan M.S. A simple time delay model for eukaryotic cell cycle. J. Theor. Biol. 2006;241:617-627.</mixed-citation><mixed-citation xml:lang="en">Srividhya J., Gopinathan M.S. A simple time delay model for eukaryotic cell cycle. J. Theor. Biol. 2006;241:617-627.</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Suzuki Y., Lu M., Ben-Jacob E., Onuchic J.N. Periodic, quasi-periodic and chaotic dynamics in simple gene elements with time delays. Sci. Rep. 2016;6:21037. DOI 10.1038/srep21037.</mixed-citation><mixed-citation xml:lang="en">Suzuki Y., Lu M., Ben-Jacob E., Onuchic J.N. Periodic, quasi-periodic and chaotic dynamics in simple gene elements with time delays. Sci. Rep. 2016;6:21037. DOI 10.1038/srep21037.</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Yang Q., Ferrell J.E., Jr. The Cdk1-APC/C cell cycle oscillator circuit functions as a time-delayed, ultrasensitive switch. Nat. Cell Biol. 2013;15:519-525.</mixed-citation><mixed-citation xml:lang="en">Yang Q., Ferrell J.E., Jr. The Cdk1-APC/C cell cycle oscillator circuit functions as a time-delayed, ultrasensitive switch. Nat. Cell Biol. 2013;15:519-525.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
