Specification of spatial relationships in directed graphs of cell signaling networks

Graph theory provides a useful and powerful tool for the analysis of cellular signaling networks. Intracellular components such as cytoplasmic signaling proteins, transcription factors and genes are connected by links, representing various types of chemical interactions that result in functional consequences. However, these graphs lack important information regarding the spatial distribution of cellular components. The ability of two cellular components to interact depends not only on their mutual chemical affinity but also on co-localization to the same subcellular region. Localization of components is often used as a regulatory mechanism to achieve specific effects in response to different receptor signals. Here we describe an approach for incorporating spatial distribution into graphs, and for the development of mixed graphs where links are specified by mutual chemical affinity as well as colocalization. We suggest that such mixed graphs will provide more accurate descriptions of functional cellular networks and their regulatory capabilities and aid in the development of large-scale predictive models of cellular behavior

The formation of H_2 and HD with the master equation approach

The formation of H2 and HD molecules on interstellar dust grains is studied using rate equation and master equation models. Rate equations are used in the analysis of laboratory experiments which examine the formation of molecular hydrogen on astrophysically relevant surfaces. However, under interstellar conditions, rate equations are not suitable for the calculation of reaction rates on dust-grain surfaces. Due to the low flux and the sub-micron size of the grains, the populations of H and D atoms on a single grain are likely to be small. In this case the reaction rates are dominated by fluctuations and should be calculated using stochastic methods. The rate of molecular hydrogen formation in interstellar clouds is evaluated using the master equation, taking into account the distribution of grain sizes.Comment: 10 pages, 2 figures. IAU symposium 231 conference proceeding

An "All Possible Steps" Approach to the Accelerated Use of Gillespie's Algorithm

Many physical and biological processes are stochastic in nature. Computational models and simulations of such processes are a mathematical and computational challenge. The basic stochastic simulation algorithm was published by D. Gillespie about three decades ago [D.T. Gillespie, J. Phys. Chem. {\bf 81}, 2340, (1977)]. Since then, intensive work has been done to make the algorithm more efficient in terms of running time. All accelerated versions of the algorithm are aimed at minimizing the running time required to produce a stochastic trajectory in state space. In these simulations, a necessary condition for reliable statistics is averaging over a large number of simulations. In this study I present a new accelerating approach which does not alter the stochastic algorithm, but reduces the number of required runs. By analysis of collected data I demonstrate high precision levels with fewer simulations. Moreover, the suggested approach provides a good estimation of statistical error, which may serve as a tool for determining the number of required runs.Comment: Accepted for publication at the Journal of Chemical Physics. 19 pages, including 2 Tables and 4 Figure

The effect of grain size distribution on H2_2 formation rate in the interstellar medium

The formation of molecular hydrogen in the interstellar medium takes place on the surfaces of dust grains. Hydrogen molecules play a role in gas-phase reactions that produce other molecules, some of which serve as coolants during gravitational collapse and star formation. Thus, the evaluation of the roduction rate of hydrogen molecules and its dependence on the physical conditions in the cloud are of great importance. Interstellar dust grains exhibit a broad size distribution in which the small grains capture most of the surface area. Recent studies have shown that the production efficiency strongly depends on the grain composition and temperature as well as on its size. In this paper we present a formula which provides the total production rate of H$_2$ per unit volume in the cloud, taking into account the grain composition and temperature as well as the grain size distribution. The formula agrees very well with the master equation results. It shows that for a physically relevant range of grain temperatures, the production rate of H$_2$ is significantly enhanced due to their broad size distribution.Comment: to appear in MNRA

Scaling anomalies in the coarsening dynamics of fractal viscous fingering patterns

We analyze a recent experiment of Sharon \textit{et al.} (2003) on the coarsening, due to surface tension, of fractal viscous fingering patterns (FVFPs) grown in a radial Hele-Shaw cell. We argue that an unforced Hele-Shaw model, a natural model for that experiment, belongs to the same universality class as model B of phase ordering. Two series of numerical simulations with model B are performed, with the FVFPs grown in the experiment, and with Diffusion Limited Aggregates, as the initial conditions. We observed Lifshitz-Slyozov scaling $t^{1/3}$ at intermediate distances and very slow convergence to this scaling at small distances. Dynamic scale invariance breaks down at large distances.Comment: 4 pages, 4 eps figures; to appear in Phys. Rev.