edoc: No conditions. Results ordered -Date Deposited. 2024-10-12T22:25:42ZEPrintshttps://edoc.unibas.ch/images/uni-logo.jpghttps://edoc.unibas.ch/2017-07-20T07:44:00Z2022-02-28T18:08:20Zhttps://edoc.unibas.ch/id/eprint/51975This item is in the repository with the URL: https://edoc.unibas.ch/id/eprint/519752017-07-20T07:44:00ZAn open-loop approach to calculate noise-induced transitionsBistability permits the co-existence of two distinct cell fates in a population of genetically identical cells. Noise induced transitions between two fates of a bistable system are difficult to calculate due to the intricate interplay between nonlinear dynamics and noise in bistable positive feedback loops. Here we opened multivariable feedback loops at the slowest variable to obtain the open-loop function and the fluctuations in the open-loop output. By the subsequent reclosing of the loop, we calculated the mean first passage time (MFPT) using the Fokker-Planck equation in good agreement with the exact stochastic simulation. When an external component interacts with a feedback component, it amplifies the extrinsic noise in the loop. Consequently, the open-loop function is shifted and the transition rates between the two states in the closed loop are increased. Despite this shift, the open-loop output reflects the system faithfully to predict the MFPT in the feedback loop. Therefore, the open-loop approach can help theoretical analysis. Furthermore, the measurement of the mean value, variance, and the reaction time-scale of the open-loop output permits the prediction of MFPT simply from experimental data, which underscores the practical value of the stochastic open-loop approach. Farzaneh MalekiAttila Becskei2017-01-03T10:05:57Z2022-02-08T18:11:47Zhttps://edoc.unibas.ch/id/eprint/43805This item is in the repository with the URL: https://edoc.unibas.ch/id/eprint/438052017-01-03T10:05:57ZContribution of bistability and noise to cell fate transitions determined by feedback openingAlternative cell fates represent a form of non-genetic diversity, which can promote adaptation and functional specialization. It is difficult to predict the rate of the transition between two cell fates due to the strong effect of noise on feedback loops and missing parameters. We opened synthetic positive feedback loops experimentally to obtain open-loop functions. These functions allowed us to identify a deterministic model of bistability by bypassing noise and the requirement to resolve individual processes in the loop. Combining the open-loop function with kinetic measurements and re-introducing the measured noise, we were able to predict the transition rates for the feedback systems without parameter tuning. Noise in gene expression was the key determinant of the transition rates inside the bistable range. Transitions between two cell fates were also observed outside of the bistable range, evidenced by bimodality and hysteresis. In this case, a slow transient process was the rate limiting step in the transitions. Thus, feedback opening is an effective approach to identify the determinants of cell fate transitions and to predict their rates. Chieh HsuVincent JaquetFarzaneh MalekiAttila Becskei2016-09-26T12:40:30Z2018-01-22T15:52:38Zhttps://edoc.unibas.ch/id/eprint/43860This item is in the repository with the URL: https://edoc.unibas.ch/id/eprint/438602016-09-26T12:40:30ZAn open-loop approach to study the stochastic propertiesRandomness is an inevitable aspect of biological networks. It has been long accepted that variability of components in a network can propagate throughout the network. In this thesis, we introduce a method that allows us to decompose the total variability of a single component into individual contributions from the other components in a network. Our method of noise decomposition helps us investigate key parameters and their relative impact on the total normalized noise and also allows us to illustrate the importance of different system modifications by adding or omitting biological processes. With our generally applicable noise decomposition method, we are able to determine the strength of individual correlations induced by different co-regulation processes that connect different components of a network. In bistable systems, variability can occur through stochastic transitions from one steady state to another. Noise induced transitions between two steady states are difficult to calculate due to the intricate interplay between nonlinear dynamics and noise in bistable positive feedback loops. We open multicomponent feedback loops at the slowest variables in order to calculate the transition rates from one steady state to another. By reclosing the feedback loop, we calculate the mean first passage time (MFPT) using the Fokker-Planck equation. It is important to emphasize that the accurate approximation of the open-loop results is not a sufficient condition for a good prediction of the MFPT. We show that only the opening at the slowest variable warrants an accurate prediction of MFPT. Multiplicative interactions among different components can introduce correlations among noises. We show that the introduced correlations affect the mean and variance of the open loop function and consequently increase the transition rate between two steady states in the closed-loop system. Our results indicate that the open-loop approach can contribute to the theoretical prediction of the MFPT. The theoretical results are shown to be in good agreement with the results of stochastic simulation. Farzaneh Maleki