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Search Results: 1 - 4 of 4 matches for " Visakan Kadirkamanathan "
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Parameter estimation and inference for stochastic reaction-diffusion systems: application to morphogenesis in D. melanogaster
Michael A Dewar, Visakan Kadirkamanathan, Manfred Opper, Guido Sanguinetti
BMC Systems Biology , 2010, DOI: 10.1186/1752-0509-4-21
Abstract: We present a Bayesian inference approach to solve both the parameter and state estimation problem for stochastic reaction-diffusion systems. This allows a determination of the full posterior distribution of the parameters (expected values and uncertainty). We benchmark the method by illustrating it on a simple synthetic experiment. We then test the method on real data about the diffusion of the morphogen Bicoid in Drosophila melanogaster. The results show how the precision with which parameters can be inferred varies dramatically, indicating that the ability to infer full posterior distributions on the parameters can have important experimental design consequences.The results obtained demonstrate the feasibility and potential advantages of applying a Bayesian approach to parameter estimation in stochastic reaction-diffusion systems. In particular, the ability to estimate credibility intervals associated with parameter estimates can be precious for experimental design. Further work, however, will be needed to ensure the method can scale up to larger problems.Reaction-diffusion systems play a fundamental role in modelling spatio-temporal dynamics in systems biology. Originally introduced by Turing [1] over 50 years ago to provide a microscopic explanation of morphogenesis, they have been extensively used to explain pattern and organ formation in animals and plants [2,3], as well as other spatio-temporal processes such as quorum sensing in bacterial biofilms [4]. The deterministic reaction-diffusion system is given by a system of partial-differential equationswhere Δ represents the Laplacian operator (second derivative in the spatial directions). Here, c is a vector of concentrations of chemical species, D is a diagonal matrix of diffusion coefficients and f encodes the reaction terms between different species.An example of a systems biology application of this type of models is the formation of morphogen gradients during development. In the simplest case, c represents
Prepatterning in the Stem Cell Compartment
Peter D. Tonge,Victor Olariu,Daniel Coca,Visakan Kadirkamanathan,Kelly E. Burrell,Stephen A. Billings,Peter W. Andrews
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0010901
Abstract: The mechanism by which an apparently uniform population of cells can generate a heterogeneous population of differentiated derivatives is a fundamental aspect of pluripotent and multipotent stem cell behaviour. One possibility is that the environment and the differentiation cues to which the cells are exposed are not uniform. An alternative, but not mutually exclusive possibility is that the observed heterogeneity arises from the stem cells themselves through the existence of different interconvertible substates that pre-exist before the cells commit to differentiate. We have tested this hypothesis in the case of apparently homogeneous pluripotent human embryonal carcinoma (EC) stem cells, which do not follow a uniform pattern of differentiation when exposed to retinoic acid. Instead, they produce differentiated progeny that include both neuronal and non-neural phenotypes. Our results suggest that pluripotent NTERA2 stem cells oscillate between functionally distinct substates that are primed to select distinct lineages when differentiation is induced.
Drift-Diffusion Analysis of Neutrophil Migration during Inflammation Resolution in a Zebrafish Model
Geoffrey R. Holmes,Giles Dixon,Sean R. Anderson,Constantino Carlos Reyes-Aldasoro,Philip M. Elks,Stephen A. Billings,Moira K. B. Whyte,Visakan Kadirkamanathan,Stephen A. Renshaw
Advances in Hematology , 2012, DOI: 10.1155/2012/792163
Abstract: Neutrophils must be removed from inflammatory sites for inflammation to resolve. Recent work in zebrafish has shown neutrophils can migrate away from inflammatory sites, as well as die in situ. The signals regulating the process of reverse migration are of considerable interest, but remain unknown. We wished to study the behaviour of neutrophils during reverse migration, to see whether they moved away from inflamed sites in a directed fashion in the same way as they are recruited or whether the inherent random component of their migration was enough to account for this behaviour. Using neutrophil-driven photoconvertible Kaede protein in transgenic zebrafish larvae, we were able to specifically label neutrophils at an inflammatory site generated by tailfin transection. The locations of these neutrophils over time were observed and fitted using regression methods with two separate models: pure-diffusion and drift-diffusion equations. While a model hypothesis test (the F-test) suggested that the datapoints could be fitted by the drift-diffusion model, implying a fugetaxis process, dynamic simulation of the models suggested that migration of neutrophils away from a wound is better described by a zero-drift, “diffusion” process. This has implications for understanding the mechanisms of reverse migration and, by extension, neutrophil retention at inflammatory sites. 1. Introduction The fate of neutrophils following completion of the inflammatory programme is of critical importance for the outcome of episodes of acute inflammation and can determine whether there is prompt healing of a wound or the development of chronic inflammation and tissue injury. Neutrophils recruited to sites of inflammation may leave the site or die in situ [1]. The most widely accepted mechanism of neutrophil disposal is the programmed cell death or apoptosis, of the neutrophil followed by macrophage uptake and clearance (reviewed in [2]). Recently, other routes have been proposed; neutrophils may move away from the inflamed site into the bloodstream (“reverse transmigration” [3]), by migration through other tissues (“retrograde chemotaxis” or “reverse migration” [4–6]), or be lost into the inflammatory exudate [7, 8]. Current understanding of the process of reverse migration is reviewed elsewhere [9]. The uncertainty as to the in vivo fates of individual cells relates in part to the difficulty in following individual cells during inflammation resolution in vivo. The transgenic zebrafish model is emerging as a key model for the study of vertebrate immunity [10] and allows direct
The Neutrophil's Eye-View: Inference and Visualisation of the Chemoattractant Field Driving Cell Chemotaxis In Vivo
Visakan Kadirkamanathan, Sean R. Anderson, Stephen A. Billings, Xiliang Zhang, Geoffrey R. Holmes, Constantino C. Reyes-Aldasoro, Philip M. Elks, Stephen A. Renshaw
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0035182
Abstract: As we begin to understand the signals that drive chemotaxis in vivo, it is becoming clear that there is a complex interplay of chemotactic factors, which changes over time as the inflammatory response evolves. New animal models such as transgenic lines of zebrafish, which are near transparent and where the neutrophils express a green fluorescent protein, have the potential to greatly increase our understanding of the chemotactic process under conditions of wounding and infection from video microscopy data. Measurement of the chemoattractants over space (and their evolution over time) is a key objective for understanding the signals driving neutrophil chemotaxis. However, it is not possible to measure and visualise the most important contributors to in vivo chemotaxis, and in fact the understanding of the main contributors at any particular time is incomplete. The key insight that we make in this investigation is that the neutrophils themselves are sensing the underlying field that is driving their action and we can use the observations of neutrophil movement to infer the hidden net chemoattractant field by use of a novel computational framework. We apply the methodology to multiple in vivo neutrophil recruitment data sets to demonstrate this new technique and find that the method provides consistent estimates of the chemoattractant field across the majority of experiments. The framework that we derive represents an important new methodology for cell biologists investigating the signalling processes driving cell chemotaxis, which we label the neutrophils eye-view of the chemoattractant field.
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