RuleMonkey: software for stochastic simulation of rule-based models

<p>Abstract</p> <p>Background</p> <p>The system-level dynamics of many molecular interactions, particularly protein-protein interactions, can be conveniently represented using reaction rules, which can be specified using model-specification languages, such as the BioNetGen language (BNGL). A set of rules implicitly defines a (bio)chemical reaction network. The reaction network implied by a set of rules is often very large, and as a result, generation of the network implied by rules tends to be computationally expensive. Moreover, the cost of many commonly used methods for simulating network dynamics is a function of network size. Together these factors have limited application of the rule-based modeling approach. Recently, several methods for simulating rule-based models have been developed that avoid the expensive step of network generation. The cost of these "network-free" simulation methods is independent of the number of reactions implied by rules. Software implementing such methods is now needed for the simulation and analysis of rule-based models of biochemical systems.</p> <p>Results</p> <p>Here, we present a software tool called RuleMonkey, which implements a network-free method for simulation of rule-based models that is similar to Gillespie's method. The method is suitable for rule-based models that can be encoded in BNGL, including models with rules that have global application conditions, such as rules for intramolecular association reactions. In addition, the method is rejection free, unlike other network-free methods that introduce null events, i.e., steps in the simulation procedure that do not change the state of the reaction system being simulated. We verify that RuleMonkey produces correct simulation results, and we compare its performance against DYNSTOC, another BNGL-compliant tool for network-free simulation of rule-based models. We also compare RuleMonkey against problem-specific codes implementing network-free simulation methods.</p> <p>Conclusions</p> <p>RuleMonkey enables the simulation of rule-based models for which the underlying reaction networks are large. It is typically faster than DYNSTOC for benchmark problems that we have examined. RuleMonkey is freely available as a stand-alone application <url>http://public.tgen.org/rulemonkey</url>. It is also available as a simulation engine within GetBonNie, a web-based environment for building, analyzing and sharing rule-based models.</p

STUDY OF MECHANICAL PROPERTIES, MICROSTRUCTURE AND RESIDUAL STRESS BY X-RAY DIFFRACTION IN WELDED JOINTS OF DUPLEX STEEL UNS S 31803 BY COATED ELECTRODE

Duplex stainless steels are widely used in the chemical, nuclear and oil and gas industries. They have an austenitic-ferritic microstructure, in equal parts. In this work, the impacts on the mechanical properties, on the metallographic behavior and the analysis of the residual stresses caused after the welding process by coated electrode were analyzed. In these analyses, a specimen produced from a 10 mm thick duplex sheet was welded, and tensile tests, micrography and residual stress analysis by x-ray diffraction were carried out. The tensile test results showed values higher than those required by the material's manufacturing standard. The specimens broke in the base metal during the tests, indicating that the welding parameters were properly specified and applied to the specimen. The metallographic analysis showed an increase in the ferritic phase in the weld region, which makes this region susceptible to pitting corrosion in environments containing chlorides. Residual stress analysis showed tensile stresses in the weld bead, in the longitudinal and transverse directions, and in the HAZ and in the root compressive stresses in the transverse direction and tensile stresses in the longitudinal direction. These stresses must be considered in the design of equipment and structures manufactured from this steel and when using coated electrode welding, to avoid premature failure, especially fatigue failure

Time and length scales of autocrine signals in three dimensions

A model of autocrine signaling in cultures of suspended cells is developed on the basis of the effective medium approximation. The fraction of autocrine ligands, the mean and distribution of distances traveled by paracrine ligands before binding, as well as the mean and distribution of the ligand lifetime are derived. Interferon signaling by dendritic immune cells is considered as an illustration.Comment: 15 page

SARS-CoV-2 infection with bilateral intralabyrinthine hemorrhage

A 47-year-old woman presented with the complaint of sudden hearing loss associated with vertigo. Serological testing was positive for IgM and negative for IgG COVID-19 antibodies, with no other associated factors. Magnetic resonance imaging of the brain showed bilateral intralabyrinthine hemorrhage

Kinetic Monte Carlo Method for Rule-based Modeling of Biochemical Networks

We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the molecular components involved in a transformation, how these components change, conditions that affect whether a transformation occurs, and a rate law. The computational cost of the method, unlike conventional simulation approaches, is independent of the number of possible reactions, which need not be specified in advance or explicitly generated in a simulation. To demonstrate the method, we apply it to study the kinetics of multivalent ligand-receptor interactions. We expect the method will be useful for studying cellular signaling systems and other physical systems involving aggregation phenomena.Comment: 18 pages, 5 figure

Rule-based modelling provides an extendable framework for comparing candidate mechanisms underpinning clathrin polymerisation

Abstract Polymerisation of clathrin is a key process that underlies clathrin-mediated endocytosis. Clathrin-coated vesicles are responsible for cell internalization of external substances required for normal homeostasis and life –sustaining activity. There are several hypotheses describing formation of closed clathrin structures. According to one of the proposed mechanisms cage formation may start from a flat lattice buildup on the cellular membrane, which is later transformed into a curved structure. Creation of the curved surface requires rearrangement of the lattice, induced by additional molecular mechanisms. Different potential mechanisms require a modeling framework that can be easily modified to compare between them. We created an extendable rule-based model that describes polymerisation of clathrin molecules and various scenarios of cage formation. Using Global Sensitivity Analysis (GSA) we obtained parameter sets describing clathrin pentagon closure and the emergence/production and closure of large-size clathrin cages/vesicles. We were able to demonstrate that the model can reproduce budding of the clathrin cage from an initial flat array

Exact Hybrid Particle/Population Simulation of Rule-Based Models of Biochemical Systems

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility. © 2014 Hogg et al

A Density-Dependent Switch Drives Stochastic Clustering and Polarization of Signaling Molecules

Positive feedback plays a key role in the ability of signaling molecules to form highly localized clusters in the membrane or cytosol of cells. Such clustering can occur in the absence of localizing mechanisms such as pre-existing spatial cues, diffusional barriers, or molecular cross-linking. What prevents positive feedback from amplifying inevitable biological noise when an un-clustered “off” state is desired? And, what limits the spread of clusters when an “on” state is desired? Here, we show that a minimal positive feedback circuit provides the general principle for both suppressing and amplifying noise: below a critical density of signaling molecules, clustering switches off; above this threshold, highly localized clusters are recurrently generated. Clustering occurs only in the stochastic regime, suggesting that finite sizes of molecular populations cannot be ignored in signal transduction networks. The emergence of a dominant cluster for finite numbers of molecules is partly a phenomenon of random sampling, analogous to the fixation or loss of neutral mutations in finite populations. We refer to our model as the “neutral drift polarity model.” Regulating the density of signaling molecules provides a simple mechanism for a positive feedback circuit to robustly switch between clustered and un-clustered states. The intrinsic ability of positive feedback both to create and suppress clustering is a general mechanism that could operate within diverse biological networks to create dynamic spatial organization

Les eaux stagnantes : Une catastrophe écologique en Union soviétique

Andrei Monine, Stagnant Waters in the USSR The closing of the straits of Kara-Bogaz, the catastrophe of the Aral Sea, the transformation of millions of acres of land into marshes — these are some of the most tangible results of absurb, bureaucratic management of water resources in the Soviet Union. It is a management which has not produced any positive results. These ecological catastrophes however have not convinced the partisans of major hydralic projects in Siberia to give up their destructive plans. Non-treated waste from the large cities and from industry, such as cellulose by-products from Baikal, like the run-off from the use of chemicals in agriculture, poisons water and accelerates the eutrophization of the lakes. It is urgent that a commission be empowered to carry-out on of the most noble combats of our time, the combat fur the ecological security of our planet.Fermeture du détroit de Kara-Bogaz, catastrophe de la mer d'Aral, transformation de millions d'hectares de terres en marécages,... sont parmi les résultats les plus tangibles d'une gestion absurde et bureaucratique des ressources en eau de l'Union soviétique, gestion dont par ailleurs les résultats économiques et sociaux sont nuls. Ces catastrophes écologiques n'ont toujours pas convaincu les partisans du détournement des fleuves sibériens de renoncer à leurs funestes projets. Les rejets non traités des égouts des grandes villes, ceux de la grande industrie tel le combinat de cellulose du Baikal , comme le lessivage des produits chimiques massivement utilisés en agriculture empoisonnent l'eau et accélèrent l'eutrophisation des lacs. Il devient urgent qu'une commission dispose de pouvoirs étendus pour assumer l'un des combats les plus nobles de notre temps, le combat pour la sécurité écologique de notre Terre.Monine André, Paillard Denis. Les eaux stagnantes : Une catastrophe écologique en Union soviétique. In: L'Homme et la société, N. 91-92, 1989. Le rappport à la nature. pp. 87-100