4 results on '"Michailova, Anushka"'
Search Results
2. Embedding optimization in computational science workflows.
- Author
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Abramson, David, Bethwaite, Blair, Enticott, Colin, Garic, Slavisa, Peachey, Tom, Michailova, Anushka, and Amirriazi, Saleh
- Subjects
PARALLEL computers ,AUTOMATIC identification ,INTELLIGENT agents ,INDUSTRIAL engineering - Abstract
Abstract: Workflows support the automation of scientific processes, providing mechanisms that underpin modern computational science. They facilitate access to remote instruments, databases and parallel and distributed computers. Importantly, they allow software pipelines that perform multiple complex simulations (leveraging distributed platforms), with one simulation driving another. Such an environment is ideal for computational science experiments that require the evaluation of a range of different scenarios “in silico” in an attempt to find ones that optimize a particular outcome. However, in general, existing workflow tools do not incorporate optimization algorithms, and thus whilst users can specify simulation pipelines, they need to invoke the workflow as a stand-alone computation within an external optimization tool. Moreover, many existing workflow engines do not leverage parallel and distributed computers, making them unsuitable for executing computational science simulations. To solve this problem, we have developed a methodology for integrating optimization algorithms directly into workflows. We implement a range of generic actors for an existing workflow system called Kepler, and discuss how they can be combined in flexible ways to support various different design strategies. We illustrate the system by applying it to an existing bio-engineering design problem running on a Grid of distributed clusters. [ABSTRACT FROM AUTHOR]
- Published
- 2010
- Full Text
- View/download PDF
3. Modeling β-Adrenergic Control of Cardiac Myocyte Contractility in Silico.
- Author
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Saucerman, Jeffrey J., Brunton, Laurence L., Michailova, Anushka P., and McCulloch, Andrew D.
- Subjects
- *
SYMPATHOMIMETIC agents , *MUSCLE cells , *CARDIAC contraction - Abstract
The β-adrenergic signaling pathway regulates cardiac myocyte contractility through a combination of feedforward and feedback mechanisms. We used systems analysis to investigate how the components and topology of this signaling network permit neurohormonal control of excitation-contraction coupling in the rat ventricular myocyte. A kinetic model integrating β-adrenergic signaling with excitation-contraction coupling was formulated, and each subsystem was validated with independent biochemical and physiological measurements. Model analysis was used to investigate quantitatively the effects of specific molecular perturbations. 3-Fold overexpression of adenylyl cyclase in the model allowed an 85% higher rate of cyclic AMP synthesis than an equivalent overexpression of β[sub 1]-adrenergic receptor, and manipulating the affinity of G[sub s]α for adenylyl cyclase was a more potent regulator of cyclic AMP production. The model predicted that less than 40% of adenylyl cyclase molecules may be stimulated under maximal receptor activation, and an experimental protocol is suggested for validating this prediction. The model also predicted that the endogenous heat-stable protein kinase inhibitor may enhance basal cyclic AMP buffering by 68% and increasing the apparent Hill coefficient of protein kinase A activation from 1.0 to 2.0. Finally, phosphorylation of the L-type calcium channel and phospholamban were found sufficient to predict the dominant changes in myocyte contractility, including a 2.6× increase in systolic calcium (inotropy) and a 28% decrease in calcium half-relaxation time (lusitropy). By performing systems analysis, the consequences of molecular perturbations in the β-adrenergic signaling network may be understood within the context of integrative cellular physiology. [ABSTRACT FROM AUTHOR]
- Published
- 2003
- Full Text
- View/download PDF
4. Slow Calcium-Depolarization-Calcium waves may initiate fast local depolarization waves in ventricular tissue
- Author
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Tveito, Aslak, Lines, Glenn Terje, Edwards, Andrew G., Maleckar, Mary M., Michailova, Anushka, Hake, Johan, and McCulloch, Andrew
- Subjects
- *
MUSCLE cells , *MYOCARDIUM , *MUSCLE contraction , *GAP junctions (Cell biology) , *HEART ventricles , *PHYSIOLOGICAL effects of calcium , *HEART cells - Abstract
Abstract: Intercellular calcium waves in cardiac myocytes are a well-recognized, if incompletely understood, phenomenon. In a variety of preparations, investigators have reported multi-cellular calcium waves or triggered propagated contractions, but the mechanisms of propagation and pathological importance of these events remain unclear. Here, we review existing experimental data and present a computational approach to investigate the mechanisms of multi-cellular calcium wave propagation. Over the past 50 years, the standard modeling paradigm for excitable cardiac tissue has seen increasingly detailed models of the dynamics of individual cells coupled in tissue solely by intercellular and interstitial current flow. Although very successful, this modeling regime has been unable to capture two important phenomena: 1) the slow intercellular calcium waves observed experimentally, and 2) how intercellular calcium events resulting in delayed after depolarizations at the cellular level could overcome a source-sink mismatch to initiate depolarization waves in tissue. In this paper, we introduce a mathematical model with subcellular spatial resolution, in which we allow both inter- and intracellular current flow and calcium diffusion. In simulations of coupled cells employing this model, we observe: a) slow inter-cellular calcium waves propagating at about 0.1 mm/s, b) faster Calcium-Depolarization-Calcium (CDC) waves, traveling at about 1 mm/s, and c) CDC-waves that can set off fast depolarization-waves (50 cm/s) in tissue with varying gap-junction conductivity. [Copyright &y& Elsevier]
- Published
- 2012
- Full Text
- View/download PDF
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