{"title":"生物化学网络内禀噪声随机振荡的振幅分布。","authors":"Moritz Lang, Steffen Waldherr, Frank Allgöwer","doi":"10.1186/1757-5036-2-10","DOIUrl":null,"url":null,"abstract":"<p><p> Intrinsic noise is a common phenomenon in biochemical reaction networks and may affect the occurence and amplitude of sustained oscillations in the states of the network. To evaluate properties of such oscillations in the time domain, it is usually required to conduct long-term stochastic simulations, using for example the Gillespie algorithm. In this paper, we present a new method to compute the amplitude distribution of the oscillations without the need for long-term stochastic simulations. By the derivation of the method, we also gain insight into the structural features underlying the stochastic oscillations. The method is applicable to a wide class of non-linear stochastic differential equations that exhibit stochastic oscillations. The application is exemplified for the MAPK cascade, a fundamental element of several biochemical signalling pathways. This example shows that the proposed method can accurately predict the amplitude distribution for the stochastic oscillations even when using further computational approximations.PACS Codes: 87.10.Mn, 87.18.Tt, 87.18.VfMSC Codes: 92B05, 60G10, 65C30.</p>","PeriodicalId":88297,"journal":{"name":"PMC biophysics","volume":"2 1","pages":"10"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/1757-5036-2-10","citationCount":"10","resultStr":"{\"title\":\"Amplitude distribution of stochastic oscillations in biochemical networks due to intrinsic noise.\",\"authors\":\"Moritz Lang, Steffen Waldherr, Frank Allgöwer\",\"doi\":\"10.1186/1757-5036-2-10\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p> Intrinsic noise is a common phenomenon in biochemical reaction networks and may affect the occurence and amplitude of sustained oscillations in the states of the network. To evaluate properties of such oscillations in the time domain, it is usually required to conduct long-term stochastic simulations, using for example the Gillespie algorithm. In this paper, we present a new method to compute the amplitude distribution of the oscillations without the need for long-term stochastic simulations. By the derivation of the method, we also gain insight into the structural features underlying the stochastic oscillations. The method is applicable to a wide class of non-linear stochastic differential equations that exhibit stochastic oscillations. The application is exemplified for the MAPK cascade, a fundamental element of several biochemical signalling pathways. This example shows that the proposed method can accurately predict the amplitude distribution for the stochastic oscillations even when using further computational approximations.PACS Codes: 87.10.Mn, 87.18.Tt, 87.18.VfMSC Codes: 92B05, 60G10, 65C30.</p>\",\"PeriodicalId\":88297,\"journal\":{\"name\":\"PMC biophysics\",\"volume\":\"2 1\",\"pages\":\"10\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1186/1757-5036-2-10\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PMC biophysics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/1757-5036-2-10\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PMC biophysics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/1757-5036-2-10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Amplitude distribution of stochastic oscillations in biochemical networks due to intrinsic noise.
Intrinsic noise is a common phenomenon in biochemical reaction networks and may affect the occurence and amplitude of sustained oscillations in the states of the network. To evaluate properties of such oscillations in the time domain, it is usually required to conduct long-term stochastic simulations, using for example the Gillespie algorithm. In this paper, we present a new method to compute the amplitude distribution of the oscillations without the need for long-term stochastic simulations. By the derivation of the method, we also gain insight into the structural features underlying the stochastic oscillations. The method is applicable to a wide class of non-linear stochastic differential equations that exhibit stochastic oscillations. The application is exemplified for the MAPK cascade, a fundamental element of several biochemical signalling pathways. This example shows that the proposed method can accurately predict the amplitude distribution for the stochastic oscillations even when using further computational approximations.PACS Codes: 87.10.Mn, 87.18.Tt, 87.18.VfMSC Codes: 92B05, 60G10, 65C30.