| 11. |
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| 12. |
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| 13. |
- Hertz, John, et al.
(author)
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Stochastic activation in a genetic switch model
- 2018
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In: Physical review. E. - 2470-0045 .- 2470-0053. ; 98:5
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Journal article (peer-reviewed)abstract
- We study a biological autoregulation process, involving a protein that enhances its own transcription, in a parameter region where bistability would be present in the absence of fluctuations. We calculate the rate of fluctuation-induced rare transitions between locally stable states using a path integral formulation and Master and Chapman-Kolmogorov equations. As in simpler models for rare transitions, the rate has the form of the exponential of a quantity S-0 (a barrier) multiplied by a prefactor eta. We calculate S-0 and eta first in the bursting limit (where the ratio gamma of the protein and mRNA lifetimes is very large). In this limit, the calculation can be done almost entirely analytically, and the results are in good agreement with simulations. For finite gamma numerical calculations are generally required. However, S-0 can be calculated analytically to first order in 1/gamma, and the result agrees well with the full numerical calculation for all gamma > 1. Employing a method used previously on other problems, we find we can account qualitatively for the way the prefactor eta varies with gamma, but its value is 15-20% higher than that inferred from simulations.
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| 14. |
- Jafari-Mamaghani, Mehrdad, 1984-
(author)
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A Treatise on Measuring Wiener-Granger Causality
- 2014
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Doctoral thesis (other academic/artistic)abstract
- Wiener-Granger causality is a well-established concept of causality based on stochasticity and the flow of time, with applications in a broad array of quantitative sciences. The majority of methods used to measure Wiener-Granger causality are based on linear premises and hence insensitive to non-linear signals. Other frameworks based on non-parametric techniques are often computationally expensive and susceptible to overfitting or lack of sensitivity.In this thesis, Paper I investigates the application of linear Wiener-Granger causality to migrating cancer cell data obtained using a Systems Microscopy experimental platform. Paper II represents a review of non-parametric measures based on information theory and discusses a number of related bottlenecks and potential routes of circumvention. Paper III studies the properties of a frequently used non-parametric information theoretical measure for a class of non-Gaussian distributions. Paper IV introduces a new efficient scheme for non-parametric analysis of Wiener-Granger causality based on kernel canonical correlations, and studies the connection between this new scheme and the information theoretical approach. Lastly, Paper V draws upon the results in the preceding paper to discuss non-parametric analysis of Wiener-Granger causality in partially observed systems.Altogether, the work presented in this thesis constitutes a comprehensive review on measures of Wiener-Granger causality in general, and in particular, features new insights on efficient non-parametric analysis of Wiener-Granger causality in high-dimensional settings.
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| 15. |
- Jafari-Mamaghani, Mehrdad, 1984-, et al.
(author)
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Transfer entropy expressions for a class of non-Gaussian distributions
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Other publication (other academic/artistic)abstract
- Transfer entropy is a frequently employed measure of conditional co-dependence in non-parametric analysis of Granger causality. In this paper, we derive analytical expressions for transfer entropy for the multivariate exponential, logistic, Pareto (type I − IV) and Burr distributions. The latter two fall into the class of fat-tailed distributions with power law properties, used frequently in biological, physical and actuarial sciences. We discover that the transfer entropy expressions for all four distributions are identical and depend merely on the multivariate distribution parameter and the number of distribution dimensions. Moreover, we find that in all four cases the transfer entropies are given by the same decreasing function of distribution dimensionality.
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| 16. |
- Jafari-Mamaghani, Mehrdad, et al.
(author)
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Transfer Entropy Expressions for a Class of Non-Gaussian Distributions
- 2014
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In: Entropy. - : MDPI AG. - 1099-4300. ; 16:3, s. 1743-1755
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Journal article (peer-reviewed)abstract
- Transfer entropy is a frequently employed measure of conditional co-dependence in non-parametric analysis of Granger causality. In this paper, we derive analytical expressions for transfer entropy for the multivariate exponential, logistic, Pareto (type I - IV) and Burr distributions. The latter two fall into the class of fat-tailed distributions with power law properties, used frequently in biological, physical and actuarial sciences. We discover that the transfer entropy expressions for all four distributions are identical and depend merely on the multivariate distribution parameter and the number of distribution dimensions. Moreover, we find that in all four cases the transfer entropies are given by the same decreasing function of distribution dimensionality.
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| 17. |
- Lock, John G., et al.
(author)
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Plasticity in the Macromolecular-Scale Causal Networks of Cell Migration
- 2014
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:2, s. e90593-
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Journal article (peer-reviewed)abstract
- Heterogeneous and dynamic single cell migration behaviours arise from a complex multi-scale signalling network comprising both molecular components and macromolecular modules, among which cell-matrix adhesions and F-actin directly mediate migration. To date, the global wiring architecture characterizing this network remains poorly defined. It is also unclear whether such a wiring pattern may be stable and generalizable to different conditions, or plastic and context dependent. Here, synchronous imaging-based quantification of migration systemorganization, represented by 87 morphological and dynamic macromolecular module features, and migration system behaviour, i.e., migration speed, facilitated Granger causality analysis. We thereby leveraged natural cellular heterogeneity to begin mapping the directionally specific causal wiring between organizational and behavioural features of the cell migration system. This represents an important advance on commonly used correlative analyses that do not resolve causal directionality. We identified organizational features such as adhesion stability and adhesion F-actin content that, as anticipated, causally influenced cell migration speed. Strikingly, we also found that cell speed can exert causal influence over organizationalfeatures, including cell shape and adhesion complex location, thus revealing causality in directions contradictory to previous expectations. Importantly, by comparing unperturbed and signalling-modulated cells, we provide proof-of-principle that causal interaction patterns are in fact plastic and context dependent, rather than stable and generalizable.
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| 18. |
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| 19. |
- Nellaker, Christoffer, et al.
(author)
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Expression profiling of repetitive elements by melting temperature analysis : variation in HERV-W gag expression across human individuals and tissues
- 2009
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In: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 10, s. 532-
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Journal article (peer-reviewed)abstract
- Background: Human endogenous retroviruses (HERV) constitute approximately 8% of the human genome and have long been considered ""junk"". The sheer number and repetitive nature of these elements make studies of their expression methodologically challenging. Hence, little is known of transcription of genomic regions harboring such elements. Results: Applying a recently developed technique for obtaining high resolution melting temperature data, we examined the frequency distributions of HERV-W gag element into 13 Tm categories in human tissues. Transcripts containing HERV-W gag sequences were expressed in non-random patterns with extensive variations in the expression between both tissues, including different brain regions, and individuals. Furthermore, the patterns of such transcripts varied more between individuals in brain regions than other tissues. Conclusion: Thus, regulated expression of non-coding regions of the human genome appears to include the HERV-W family of repetitive elements. Although it remains to be established whether such expression patterns represent leakage from transcription of functional regions or specific transcription, the current approach proves itself useful for studying detailed expression patterns of repetitive regions.
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| 20. |
- Nellåker, Christoffer, et al.
(author)
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Mixture models for analysis of melting temperature data
- 2008
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In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 9:370
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Journal article (peer-reviewed)abstract
- BackgroundIn addition to their use in detecting undesired real-time PCR products, melting temperatures are useful for detecting variations in the desired target sequences. Methodological improvements in recent years allow the generation of high-resolution melting-temperature (Tm) data. However, there is currently no convention on how to statistically analyze such high-resolution Tm data.ResultsMixture model analysis was applied to Tm data. Models were selected based on Akaike's information criterion. Mixture model analysis correctly identified categories in Tm data obtained for known plasmid targets. Using simulated data, we investigated the number of observations required for model construction. The precision of the reported mixing proportions from data fitted to a preconstructed model was also evaluated.ConclusionMixture model analysis of Tm data allows the minimum number of different sequences in a set of amplicons and their relative frequencies to be determined. This approach allows Tm data to be analyzed, classified, and compared in an unbiased manner.
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