Qualitative and quantitative analysis of systems and synthetic biology constructs using P systems

YesComputational models are perceived as an attractive alternative to mathematical models (e.g., ordinary differential equations). These models incorporate a set of methods for specifying, modeling, testing, and simulating biological systems. In addition, they can be analyzed using algorithmic techniques (e.g., formal verification). This paper shows how formal verification is utilized in systems and synthetic biology through qualitative vs quantitative analysis. Here, we choose two well-known case studies: quorum sensing in P. aeruginosas and pulse generator. The paper reports verification analysis of two systems carried out using some model checking tools, integrated to the Infobiotics Workbench platform, where system models are based on stochastic P systems.EPSR

Efficient Parallel Statistical Model Checking of Biochemical Networks

We consider the problem of verifying stochastic models of biochemical networks against behavioral properties expressed in temporal logic terms. Exact probabilistic verification approaches such as, for example, CSL/PCTL model checking, are undermined by a huge computational demand which rule them out for most real case studies. Less demanding approaches, such as statistical model checking, estimate the likelihood that a property is satisfied by sampling executions out of the stochastic model. We propose a methodology for efficiently estimating the likelihood that a LTL property P holds of a stochastic model of a biochemical network. As with other statistical verification techniques, the methodology we propose uses a stochastic simulation algorithm for generating execution samples, however there are three key aspects that improve the efficiency: first, the sample generation is driven by on-the-fly verification of P which results in optimal overall simulation time. Second, the confidence interval estimation for the probability of P to hold is based on an efficient variant of the Wilson method which ensures a faster convergence. Third, the whole methodology is designed according to a parallel fashion and a prototype software tool has been implemented that performs the sampling/verification process in parallel over an HPC architecture

Modelling of Multi-Agent Systems: Experiences with Membrane Computing and Future Challenges

Formal modelling of Multi-Agent Systems (MAS) is a challenging task due to high complexity, interaction, parallelism and continuous change of roles and organisation between agents. In this paper we record our research experience on formal modelling of MAS. We review our research throughout the last decade, by describing the problems we have encountered and the decisions we have made towards resolving them and providing solutions. Much of this work involved membrane computing and classes of P Systems, such as Tissue and Population P Systems, targeted to the modelling of MAS whose dynamic structure is a prominent characteristic. More particularly, social insects (such as colonies of ants, bees, etc.), biology inspired swarms and systems with emergent behaviour are indicative examples for which we developed formal MAS models. Here, we aim to review our work and disseminate our findings to fellow researchers who might face similar challenges and, furthermore, to discuss important issues for advancing research on the application of membrane computing in MAS modelling.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314

Qualitative networks: a symbolic approach to analyze biological signaling networks

BACKGROUND: A central goal of Systems Biology is to model and analyze biological signaling pathways that interact with one another to form complex networks. Here we introduce Qualitative networks, an extension of Boolean networks. With this framework, we use formal verification methods to check whether a model is consistent with the laboratory experimental observations on which it is based. If the model does not conform to the data, we suggest a revised model and the new hypotheses are tested in-silico. RESULTS: We consider networks in which elements range over a small finite domain allowing more flexibility than Boolean values, and add target functions that allow to model a rich set of behaviors. We propose a symbolic algorithm for analyzing the steady state of these networks, allowing us to scale up to a system consisting of 144 elements and state spaces of approximately 10(86 )states. We illustrate the usefulness of this approach through a model of the interaction between the Notch and the Wnt signaling pathways in mammalian skin, and its extensive analysis. CONCLUSION: We introduce an approach for constructing computational models of biological systems that extends the framework of Boolean networks and uses formal verification methods for the analysis of the model. This approach can scale to multicellular models of complex pathways, and is therefore a useful tool for the analysis of complex biological systems. The hypotheses formulated during in-silico testing suggest new avenues to explore experimentally. Hence, this approach has the potential to efficiently complement experimental studies in biology

EuroBlight tool for the comparison of late blight sub-models - Status and perspectives

Partners from the EuroBlight network, with support from ENDURE, created a freely available platform that allows testing and comparing weather-based late blight models (www.euroblight.net). The platform contains extensive weather data: hourly data from many European Union countries, both north and south, between 2006 and 2009. It also contains seven different weather based late blight sub-models. Most recently, biological data for verification were uploaded from monitoring of field experiments and potato fields around Europe. The results from different models for disease risk or, infection risk give similar but by no means identical results. The tool is intended to improve the quality of existing sub-models and it will be used to analyse the weather based risk of late blight development in different regions of Europe and beyon

Formal Modeling of Connectionism using Concurrency Theory, an Approach Based on Automata and Model Checking

This paper illustrates a framework for applying formal methods techniques, which are symbolic in nature, to specifying and verifying neural networks, which are sub-symbolic in nature. The paper describes a communicating automata [Bowman & Gomez, 2006] model of neural networks. We also implement the model using timed automata [Alur & Dill, 1994] and then undertake a verification of these models using the model checker Uppaal [Pettersson, 2000] in order to evaluate the performance of learning algorithms. This paper also presents discussion of a number of broad issues concerning cognitive neuroscience and the debate as to whether symbolic processing or connectionism is a suitable representation of cognitive systems. Additionally, the issue of integrating symbolic techniques, such as formal methods, with complex neural networks is discussed. We then argue that symbolic verifications may give theoretically well-founded ways to evaluate and justify neural learning systems in the field of both theoretical research and real world applications

A Study of the Use of Process Simulation and Pilot-Scale Verification Trials for the Design of Bioprocesses

This thesis examines the use of process simulation tools and pilot-scale verification trials for the design of efficient bioprocesses. The use of process simulation tools requires the development of predictive, robust unit operation models were the models are used for the calculation of mass and energy balances, and ultimately economic analysis and optimisation. Verification trials are employed to assess how the model compares to reality. Models describing key unit operations such as protein precipitation and centrifugation are often very simplistic and do not take into account the added complications that biological materials present, such as hindered settling at high solids concentrations in centrifuges and susceptibility to shear forces. The generation of useful engineering models, testing by comparison with real process data and their use in design are covered in this work. Two models have been developed in this thesis; batch protein precipitation and disc-stack centrifugation. The batch protein precipitation model calculates the enzyme and total protein solubilities upon precipitant addition, together with the precipitate phase particle size distribution and enables the effects of precipitant concentration and batch ageing conditions to be predicted. A mass and activity balance is then completed around the unit operation. The disc-stack centrifuge model is capable of predicting the separation of a range of biological materials including whole yeast cell, cell debris and shear-sensitive precipitate particle suspensions. A centrifuge feedzone breakage model has also been developed, which accounts for the shear breakage of precipitate particle suspensions that occurs in the feedzone of the centrifuge. The capacity to predict the much finer particle size distribution which enters the active disc stack where particle separation occurs enables accurate predictions of separation performance to be made. The centrifuge model also enables mass and activity balances to be completed around the unit operation. The models have been linked together so that they predict mass balances around a complete process sequence for the isolation of an intracellular yeast enzyme. Pilot-scale process verification trials have been conducted for the process sequence. The simulations and experimental verification trials provide total protein concentration and ADH activity data for all streams throughout the process. In the small scale trials DNA and cell debris concentration were also measured and simulated. Results show that the simulated results follow the trends of the experimental data extremely well. The utility of verification trials in indicating where further modelling is required, such as the centrifuge feedzone is demonstrated. Process perturbation trials have been used to show that the models can be used outside their normal operating conditions. The models developed for the yeast ADH test bed have also been tested for a process for the isolation of β-galactosidase from Escherichia coli. Results have shown that only limited experimental data is required to calculate the parameters used in the models to effect an accurate simulation. This thesis demonstrates the use of a combination of modelling and experimental verification trials for the design of bioprocesses. Recommendations for future work in the areas of further model improvement and development of other unit operation models, investigation of simulation frameworks, incorporation of on-line control techniques and the use of "what-if" studies are made