Strong regulatory graphs

Logical modeling is a powerful tool in biology, offering a system-level understanding of the complex interactions that govern biological processes. A gap that hinders the scalability of logical models is the need to specify the update function of every vertex in the network depending on the status of its predecessors. To address this, we introduce in this paper the concept of strong regulation, where a vertex is only updated to active/inactive if all its predecessors agree in their influences; otherwise, it is set to ambiguous. We explore the interplay between active, inactive, and ambiguous influences in a network. We discuss the existence of phenotype attractors in such networks, where the status of some of the variables is fixed to active/inactive, while the others can have an arbitrary status, including ambiguous

THE "DOBRESCU MACROMODEL" OF THE ROMANIAN MARKET ECONOMY - 2005 VERSION YEARLY FORECAST AUTUMN FORECAST

In this article we present only the economic forecast of the variable of interest. For a description of the model, see RJEF, No. 1/2007 of [4]. The macromodel estimates the short and medium-term economic implications for internal policies and changes in the international context. This new version of the Romanian macromodel incorporates the experience accumulated through the utilisation of its previous forms - either experimental (tested during 1991-1995) or operational (developed during 1996-2003). At the same time, it introduces some methodological and information improvements. The most significant of them is the structural decomposition of the economy, associated with input-output techniques. Due to the relatively advanced stage of the transitional processes in Romania, the behavioural functions were accommodated - as much as possible - to the standard relationships. Unlike the versions that used the statistical series beginning in 1980, the present one is based exclusively on information concerning the period 1989-2004. Therefore, we have considered more adequately to name this variant the macromodel of the Romanian market (not transition, as before) economy.model, input-output analysis, econometric relationships, simulations

THE "DOBRESCU" MACROMODEL OF THE ROMANIAN MARKET ECONOMY - 2005 VERSION - YEARLY FORECAST*

The paper briefly presents the "Dobrescu" macromodel, the 2005 version, and the yearly forecast of the Romanian market economy computed on its basis. * (PHARE Programme RO2003/005-551.02.03 "Strengthening the capacity for analysis, macroeconomic forecast and elaboration of economic policies within the National Commission of Prognosis, the Ministry of Economy and Trade and the Prime Minister's Cabinet" - Romanian Center for Economic Policies, http://www.cnp.ro/site CNP.pdf. Published on the site Internet Securities Inc., ISI Emerging Markets, http://www.securities.com)macromodel, simulations, forecasting

THE "DOBRESCU MACROMODEL" OF THE ROMANIAN MARKET ECONOMY - 2005 VERSION YEARLY FORECAST AUTUMN FORECAST

In this article we present only the economic forecast of the variable of interest. For a description of the model, see RJEF, No. 1/2007 of [4]. The macromodel estimates the short and medium-term economic implications for internal policies and changes in the international context. This new version of the Romanian macromodel incorporates the experience accumulated through the utilisation of its previous forms - either experimental (tested during 1991-1995) or operational (developed during 1996-2004). At the same time, it introduces some methodological and information improvements. The most significant of them is the structural decomposition of the economy, associated with input-output techniques. Due to the relatively advanced stage of the transitional processes in Romania, the behavioural functions were accommodated - as much as possible - to the standard relationships. Unlike the versions that used the statistical series beginning in 1980, the present one is based exclusively on information concerning the period 1989-2004. Therefore, we have considered more adequately to name this variant the macromodel of the Romanian market (not transition, as before) economy.model, input-output analysis, econometric relationships, simulations

Mutual Mobile Membranes with Timers

A feature of current membrane systems is the fact that objects and membranes are persistent. However, this is not true in the real world. In fact, cells and intracellular proteins have a well-defined lifetime. Inspired from these biological facts, we define a model of systems of mobile membranes in which each membrane and each object has a timer representing their lifetime. We show that systems of mutual mobile membranes with and without timers have the same computational power. An encoding of timed safe mobile ambients into systems of mutual mobile membranes with timers offers a relationship between two formalisms used in describing biological systems

The "Dobrescu Macromodel" of the Romanian Market Economy* -2005 Version-Yearly Forecast Scenario for “Increase in foreign capital inflows”

In this article we present only the economic forecast of the variable of interest. For a description of the model, see RJEF, No. 1/2007 of [4]. The macromodel estimates the short and medium-term economic implications for internal policies and changes in the international context. This new version of the Romanian macromodel incorporates the experience accumulated through the utilisation of its previous forms - either experimental (tested during 1991-1995) or operational (developed during 1996-2003). At the same time, it introduces some methodological and information improvements. The most significant of them is the structural decomposition of the economy, associated with input-output techniques. Due to the relatively advanced stage of the transitional processes in Romania, the behavioural functions were accommodated - as much as possible - to the standard relationships. Unlike the versions that used the statistical series beginning in 1980, the present one is based exclusively on information concerning the period 1989-2004. Therefore, we have considered more adequately to name this variant the macromodel of the Romanian market (not transition, as before) economy.model, input-output analysis, econometric relationships, simulations

Quantifying the implicit process flow abstraction in SBGN-PD diagrams with Bio-PEPA

For a long time biologists have used visual representations of biochemical networks to gain a quick overview of important structural properties. Recently SBGN, the Systems Biology Graphical Notation, has been developed to standardise the way in which such graphical maps are drawn in order to facilitate the exchange of information. Its qualitative Process Diagrams (SBGN-PD) are based on an implicit Process Flow Abstraction (PFA) that can also be used to construct quantitative representations, which can be used for automated analyses of the system. Here we explicitly describe the PFA that underpins SBGN-PD and define attributes for SBGN-PD glyphs that make it possible to capture the quantitative details of a biochemical reaction network. We implemented SBGNtext2BioPEPA, a tool that demonstrates how such quantitative details can be used to automatically generate working Bio-PEPA code from a textual representation of SBGN-PD that we developed. Bio-PEPA is a process algebra that was designed for implementing quantitative models of concurrent biochemical reaction systems. We use this approach to compute the expected delay between input and output using deterministic and stochastic simulations of the MAPK signal transduction cascade. The scheme developed here is general and can be easily adapted to other output formalisms

Quantitative Model Refinement as a Solution to the Combinatorial Size Explosion of Biomodels

AbstractBuilding a large system through a systematic, step-by-step refinement of an initial abstract specification is a well established technique in software engineering, not yet much explored in systems biology. In the case of systems biology, one starts from an abstract, high-level model of a biological system and aims to add more and more details about its reactants and/or reactions, through a number of consecutive refinement steps. The refinement should be done in a quantitatively correct way, so that (some of) the numerical properties of the model (such as the experimental fit and validation) are preserved. In this study, we focus on the data-refinement mechanism where the aim is to increase the level of details of some of the reactants of a given model. That is, we analyse the case when a model is refined by substituting a given species by several types of subspecies. We show in this paper how the refined model can be systematically obtained from the original one. As a case study for this methodology we choose a recently introduced model for the eukaryotic heat shock response, [I. Petre, A. Mizera, C. L. Hyder, A. Meinander, A. Mikhailov, R.I. Morimoto, L. Sistonen, J. E. Eriksson, R.-J. Back, A simple mass-action model for the eukaryotic heat shock response and its mathematical validation, Natural Computing, 10(1), 595–612, 2011.]. We refine this model by including details about the acetylation of the heat shock factors and its influence on the heat shock response. The refined model has a significantly higher number of kinetic parameters and variables. However, we show that our methodology allows us to preserve the experimental fit/validation of the model with minimal computational effort

Scalable reaction network modeling with automatic validation of consistency in Event-B

Constructing a large biological model is a difficult, error-prone process. Small errors in writing a part of the model cascade to the system level and their sources are difficult to trace back. In this paper we extend a recent approach based on Event-B, a state-based formal method with refinement as its central ingredient, allowing us to validate for model consistency step-by-step in an automated way. We demonstrate this approach on a model of the heat shock response in eukaryotes and its scalability on a model of the ErbB signaling pathway. All consistency properties of the model were proved automatically with computer support.</p