Setting Parameters for Biological Models With ANIMO

ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions between biological entities in form of a graph, while the parameters determine the speed of occurrence of such interactions. When a mismatch is observed between the behavior of an ANIMO model and experimental data, we want to update the model so that it explains the new data. In general, the topology of a model can be expanded with new (known or hypothetical) nodes, and enables it to match experimental data. However, the unrestrained addition of new parts to a model causes two problems: models can become too complex too fast, to the point of being intractable, and too many parts marked as "hypothetical" or "not known" make a model unrealistic. Even if changing the topology is normally the easier task, these problems push us to try a better parameter fit as a first step, and resort to modifying the model topology only as a last resource. In this paper we show the support added in ANIMO to ease the task of expanding the knowledge on biological networks, concentrating in particular on the parameter settings

Computational Modeling of Complex Protein Activity Networks

Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a user-friendly computational tool, Analysis of Networks with Interactive MOdeling (ANIMO). ANIMO is a powerful tool to formalize knowledge on molecular interactions. This formalization entails giving a precise mathematical (formal) description of molecular states and of interactions between molecules. Such a model can be simulated, thereby in silico mimicking the processes that take place in the cell. In sharp contrast to classical graphical representations of molecular interaction networks, formal models allow in silico experiments and functional analysis of the dynamic behavior of the network. In addition, ANIMO was developed specifically for use by biologists who have little or no prior modeling experience. In this chapter, we guide the reader through the ANIMO workflow using osteoarthritis (OA) as a case study. WNT, IL-1β, and BMP signaling and cross talk are used as a concrete and illustrative model

Modeling Biological Pathway Dynamics With Timed Automata

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires to capture their dynamics through computational support and models. ANIMO (Analysis of Networks with Interactive MOdelling) is a tool that enables construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analysed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signalling networks. This enforces precision and uniformity in the definition of signalling pathways, contributing to the integration of isolated signalling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behaviour of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behaviour of the network components is displayed graphically, allowing for an intuitive and interactive modelling experience

A spatially distributed, physically-based modeling approach for estimating agricultural nitrate leaching to groundwater

Nitrogen-nitrate, while being fundamental for crop production, is of particular concern in the agricultural sector, as it can easily leach to the water table, worsening groundwater quality. Numerical models and Geographic Information System may support the estimation of nitrate leaching rates in space and time, to support sustainable agricultural management practices. In this paper, we present a module for the simulation of the processes involved in the nitrogen cycle in the unsaturated zone, including nitrate leaching. This module was developed taking steps from the ANIMO and EPIC model frameworks and coupled to the hydrological models integrated within the FREEWAT platform. As such, the nitrogen cycle module was then included in the FREEWAT platform. The developed module and the coupling approach were tested using a simple synthetic application, where we simulated nitrate leaching through the unsaturated zone for a sunflower crop irrigated district during a dry year. The results of the simulation allow the estimation of daily nitrate concentration values at the water table. These spatially distributed values may then be further used as input concentration in models for simulating solute transport in aquifers

Challenges in modelling dissolved organic matter dynamics in agricultural soil using DAISY

Because dissolved organic matter (DOM) plays an important role is terrestrial C-,N-and P-balances and transport of these three components to aquatic environments, there is a need to include it in models. This paper presents the concept of the newly developed DOM modules implemented in the DAISY model with focus on the quantification of DOM sorption/desorption and microbial-driven DOM turnover. The kinetics of DOM sorption/desorption is described by the deviation of the actual DOM concentration in solution from the equilibrium concentration, Ceq. The Ceq is soil specific and estimated from pedotransfer functions taking into account the soil content of organic matter, Al and Fe oxides. The turnover of several organic matter pools including one DOM pool are described by first-order kinetics. The DOM module was tested at field scale for three soil treatments applied after cultivating grass–clover swards. Suction cups were installed at depths 30, 60 and 90 cm and soil solution was sampled for quantification of dissolved organic C (DOC) and dissolved organic N (DON). In the topsoil, the observed fluctuations in DOC were successfully simulated when the sorption/desorption rate coefficient k was low. In the subsoil, the observed concentrations of DOC were steadier and the best simulations were obtained using a high k. The model shows that DOC and DON concentrations are levelled out in the subsoils due to soil buffering. The steady concentration levels were based on the Ceq for each horizon and the kinetic concept for sorption/desorption of DOC appeared aviable approach. If Ceq was successfully estimated by the pedotransfer function it was possible to simulate the DOC concentration in the subsoil. In spite of difficulties in describing the DOC dynamics of the topsoil, the DOM module simulates the subsoil concentration level of DOC well, and also — but with more uncertainty — the DON concentration level

Application and evaluation of phosphorus and nitrogen loss quantification tools

Årsliste 2004 The report may also be downloaded from EUROHARP web site: www.euroharp.org. Editors, authors and NIVA assume no liability for any loss resulting from the use of this report.The EC funded EUROHARP project encompasses 22 research institutes from 17 European countries (2002-2005). The overall objective of the EUROHARP work is to provide end-users with guidance for an appropriate choice of quantification tools to satisfy existing European requirements on harmonisation and transparency for quantifying diffuse nutrient losses, e.g. to facilitate the implementation of the Water Framework Directive and the Nitrates Directive. The project includes both the assessment of the performance of individual models and the applicability of the same models in catchments with different data availability and environmental condition throughout Europe. The basis for the performance and applicability studies is the compilation of a harmonised GIS/database for all catchment data and the analysis of these data (trends, watercourse retention).Scoumans, O. (ALTERRA, The Netherlands) Silgram, M. (ADAS, United Kingdom