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Agent based modelling is a methodology for simulating a variety of systems across a broad spectrum of fields. However, due to the complexity of the systems it is often impossible or impractical to model them at a one to one scale. In this paper we use a simple reaction rate model implemented using the FLAME framework to test the impact of common methods for reducing model complexity such as reducing scale, increasing iteration duration and reducing message overheads. We demonstrate that such approaches can have significant impact on simulation runtime albeit with increasing risk of aberrant system behaviour and errors, as the complexity of the model is reduced. [ABSTRACT FROM AUTHOR]

Abstract: One of the great benefits of using a stream X-machine to specify a system is its associated testing method. Under certain design for test conditions, this method produces a test suite that can determine the correctness of the implementation under test (IUT), provided that the processing functions of the stream X-machine specification have been correctly implemented. The method was originally developed for controllable stream X-machines. A recent paper generalizes the original method by considering specifications that do not meet the controllability requirement. However, it is still required that a controllable stream X-machine model of the IUT exists and the size of the test suite produced strongly depends on the (estimated) upper bound on the number of states of this controllable model. While this assumption is in general reasonable for most interactive systems, it may produce unmanageable test suites for even simple data processing-oriented applications. This paper provides a new variant of the stream X-machine based testing method that no longer depends on the size of a controllable model of the IUT. In data processing-oriented applications, the new method can drastically reduce the size of the test suite produced at the expense of a (possibly) more complex generation process. [Copyright &y& Elsevier]

Nature is governed by local interactions among lower-level sub-units, whether at the cell, organ, organism, or colony level. Adaptive system behaviour emerges via these interactions, which integrate the activity of the sub-units. To understand the system level it is necessary to understand the underlying local interactions. Successful models of local interactions at different levels of biological organisation, including epithelial tissue and ant colonies, have demonstrated the benefits of such 'agent-based' modelling [1-4]. Here we present an agent-based approach to modelling a crucial biological system - the intracellular NF-kB signalling pathway. The pathway is vital to immune response regulation, and is fundamental to basic survival in a range of species [5-7]. Alterations in pathway regulation underlie a variety of diseases, including atherosclerosis and arthritis. Our modelling of individual molecules, receptors and genes provides a more comprehensive outline of regulatory network mechanisms than previously possible with equation-based approaches [8]. The method also permits consideration of structural parameters in pathway regulation; here we predict that inhibition of NF-kB is directly affected by actin filaments of the cytoskeleton sequestering excess inhibitors, therefore regulating steady-state and feedback behaviour. [ABSTRACT FROM AUTHOR]

Colonies of Pheidole ambigua ants excavate soil and drop it outside the nest entrance. The deposition of thousands of loads leads to the formation of regular ring-shaped piles. How is this pattern generated? This study investigated soil pile formation on level and sloping surfaces, both empirically and using an agent-based model. We found that ants drop soil preferentially in the direction in which the slope is least steeply uphill from the nest entrance, both when adding to an existing pile and when starting a new pile. Ants respond to cues from local slope to choose downhill directions. Ants walking on a slope increase the frequency and magnitude of changes in direction, and more of these changes of direction take them downhill than uphill. Also, ants carrying soil on a slope wait longer before dropping their soil compared to ants on a level plane. These mechanisms combine to focus soil dropping in the downhill direction, without the necessity of a direct relationship between slope and probability of dropping soil. These empirically determined rules were used to simulate soil disposal. The slight preference for turning downhill measured empirically was shown in the model to be sufficient to generate biologically realistic patterns of soil dumping when combined with memory of the direction of previous trips. From simple rules governing individual behaviour an overall pattern emerges, which is appropriate to the environment and allows a rapid response to changes. [Copyright &y& Elsevier]

One of the strengths of using a stream X-machine to specify a system is that, under certain well defined conditions, it is possible to produce a test set that is guaranteed to determine the correctness of the implementation. This testing method assumes that the processing functions are correctly implemented, therefore it only tests the integration of the processing functions implementations into the system implementation. This paper uses a case study to illustrate how this method can be extended so that it will no longer require the implementations of the processing functions to be proved correct before the actual system testing can take place. Instead, the testing of the processing functions is performed along with the integration testing. [ABSTRACT FROM AUTHOR]

The Pharaoh’s ant (Monomorium pharaonis), a significant pest in many human environments, is phenomenally successful at locating and exploiting available food resources. Several pheromones are utilized in the self-organized foraging of this ant but most aspects of the overall system are poorly characterised. Agent-based modelling of ants as individual complex X-machines facilitates study of the mechanisms underlying the emergence of trails and aids understanding of the process. Conducting simultaneous modelling, and simulation, alongside empirical biological studies is shown to drive the research by formulating hypotheses that must be tested before the model can be verified and extended. Integration of newly characterised behavioural processes into the overall model will enable testing of general theories giving insight into division of labour within insect societies. This study aims to establish a new paradigm in computational modelling applicable to all types of multi-agent biological systems, from tissues to animal societies, as a powerful tool to accelerate basic research. [Copyright &y& Elsevier]

The fungus, Magnaporthe grisea (Rice blast fungus) is a major agricultural problem affecting rice and related food crops. The way that the fungus invades the host plant and propagates itself is a very important scientific problem and recent advances in research into the genetic basis of these processes can be used to build a simple partial model using hybrid computational modelling techniques. The possible potential benefits of doing this include the use of computer simulation and automated analysis through techniques such as model checking to understand the complex behaviour of such systems. The example is a metaphor for the process of trying to integrate and understand much of the vast amounts of genomic and other data that is being produced in current molecular biology research. [Copyright &y& Elsevier]

Computational models have been of interest in biology for many years and have represented a particular approach to trying to understand biological processes and phenomena from a systems point of view. Much of the early work was rather abstract and high level and probably seemed to many to be of more philosophical than practical value. There have, however, been some advances in the development of more realistic models and the current state of computer science research provides us with new opportunities through both the emergence of models that can model seriously complex systems and also the support that modern software can give to the modelling process. This paper describes a few of the early simple models¹ and then goes on to look at some new ideas in the area with a particular application drawn from the world of mycology. Some general principles relating to how new and emerging computational techniques can help to represent and understand extremely complex models conclude the paper. [ABSTRACT FROM AUTHOR]

In this paper we seek to dispel some of the myths and to address some of the real managerial issues which we believe may have deterred academics from involving commercial and industrial partners as customers in students' software project work. We contend that students know when a project is phoney, when requirements are dreamt up by academics and when the deliverables are of no practical use once a project mark has been assigned. The involvement of an external customer materially affects students' motivation, the quality of work that they produce and their sense of achievement. Put simply, authenticity is the key to a rich, challenging and meaningful educational project experience. [ABSTRACT FROM AUTHOR]

Pheromone trails are used by many ants to guide foragers between nest and food. But how does a forager that has become displaced from a trail know which way to go on rejoining the trail? A laden forager, for example, should walk towards the nest. Polarized trails would enable ants to choose the appropriate direction, thereby saving time and reducing predation risk. However, previous research has found no evidence that ants can detect polarity from the pheromone trail alone. Pharaoh's ants (Monomorium pharaonis) produce elaborate trail networks throughout their foraging environment. Here we show that by using information from the geometry of trail bifurcations within this network, foragers joining a trail can adaptively reorientate themselves if they initially walk in the wrong direction. The frequency of correct reorientations is maximized when the trail bifurcation angle is approximately 60 degrees, as found in natural networks. These are the first data to demonstrate how ant trails can themselves provide polarity information. They also demonstrate previously unsuspected sophistication in the organization and information content of networks in insect societies. [ABSTRACT FROM AUTHOR]

The transcription factor NF-κB (nuclear factor kappa B) is activated by Toll-like receptors and controlled by mechanotransduction and changes in the cytoskeleton. In this study we combine 3-D predictive protein modelling and in vitro experiments with in silico simulations to determine the role of the cytoskeleton in regulation of NF-κB. Simulations used a comprehensive agent-based model of the NF-κB pathway, which includes the type 1 IL-1 receptor (IL-1R1) complex and signalling intermediates, as well as cytoskeletal components. Agent based modelling relies on in silico reproductions of systems through the interactions of its components, and provides a reliable tool in investigations of biological processes, which require spatial considerations and involve complex formation and translocation of regulatory components. We show that our model faithfully reproduces the multiple steps comprising the NF-κB pathway, and provides a framework from which we can explore novel aspects of the system. The analysis, using 3-D predictive protein modelling and in vitro assays, demonstrated that the NF-κB inhibitor, IκBα is sequestered to the actin/spectrin complex within the cytoskeleton of the resting cell, and released during IL-1 stimulation, through a process controlled by the IL-1RI co-receptor TILRR (Toll-like and IL-1 receptor regulator). In silico simulations using the agent-based model predict that the cytoskeletal pool of IκBα is released to adjust signal amplification in relation to input levels. The results suggest that the process provides a mechanism for signal calibration and enables efficient, activation-sensitive regulation of NF-κB and inflammatory responses. [ABSTRACT FROM AUTHOR]

Grammar inference is a family of machine learning techniques that aim to infer grammars from a sample of sentences in some (unknown) language. Dynamic analysis is a family of techniques in the domain of software engineering that attempts to infer rules that govern the behaviour of software systems from a sample of executions. Despite their disparate domains, both fields have broadly similar aims; they try to infer rules that govern the behaviour of some unknown system from a sample of observations. Deriving general rules about program behaviour from dynamic analysis is difficult because it is virtually impossible to identify and supply a complete sample of necessary program executions. The problems that arise with incomplete input samples have been extensively investigated in the grammar inference community. This has resulted in a number of advances that have produced increasingly sophisticated solutions that are more successful at accurately inferring grammars from (potentially) sparse information about the underlying system. This paper investigates the similarities and shows how many of these advances can be applied with similar effect to dynamic analysis problems by a series of small experiments on random state machines. Copyright © 2008 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Background: Autologous keratincoytes are routinely expanded using irradiated mouse fibroblasts and bovine serum for clinical use. With growing concerns about the safety of these xenobiotic materials, it is desirable to culture keratinocytes in media without animal derived products. An improved understanding of epithelial/mesenchymal interactions could assist in this. Methodology/Principal Findings: A keratincyte/fibroblast o-culture model was developed by extending an agent-based keratinocyte colony formation model to include the response of keratinocytes to both fibroblasts and serum. The model was validated by comparison of the in virtuo and in vitro multicellular behaviour of keratinocytes and fibroblasts in single and co-culture in Greens medium. To test the robustness of the model, several properties of the fibroblasts were changed to investigate their influence on the multicellular morphogenesis of keratinocyes and fibroblasts. The model was then used to generate hypotheses to explore the interactions of both proliferative and growth arrested fibroblasts with keratinocytes. The key predictions arising from the model which were confirmed by in vitro experiments were that 1) the ratio of fibroblasts to keratinocytes would critically influence keratinocyte colony expansion, 2) this ratio needed to be optimum at the beginning of the co-culture, 3) proliferative fibroblasts would be more effective than irradiated cells in expanding keratinocytes and 4) in the presence of an adequate number of fibroblasts, keratinocyte expansion would be independent of serum. Conclusions: A closely associated computational and biological approach is a powerful tool for understanding complex biological systems such as the interactions between keratinocytes and fibroblasts. The key outcome of this study is the finding that the early addition of a critical ratio of proliferative fibroblasts can give rapid keratinocyte expansion without the use of irradiated mouse fibroblasts and bovine serum. [ABSTRACT FROM AUTHOR]

Pheromone trails provide a positive feedback mechanism for many animal species, and facilitate the sharing of information about food, nest or mate location. How long pheromone trails persist determines how long these environmental memories are accessible to conspecifics. We determined the time frame over which Pharaoh''s ant colonies can re-establish a long-lived trail and how the behaviour of individual workers contributes to trail re-establishment. We used artificially constrained pheromone trails on paper to investigate trail longevity and individual responses. Trails formed by traffic of 1000–2000 ant passages could be re-established after 24h, and after 48h for 4000–8000 ant passages. Only 27.5% of individual foragers were highly successful in a bioassay testing the ability to detect trails established 24h earlier. Trail-finding ability was significantly correlated with a low antennal position. Long-lived trail detection scores increased significantly in 57% of foragers after 5h of food deprivation and isolation, but declined again after feeding. In a control study, only 9% of foragers changed their scores, when isolated with food present. A high degree of conservatism was found such that, regardless of treatment, 21% always failed the bioassay and 17% always succeeded. Our demonstration of long-lived components in Pharaoh''s ant trails and of a behavioural specialization in ‘pathfinding’ shows that pheromone trails are more complex at the individual level than is generally recognized. [Copyright &y& Elsevier]

Signal transduction through the Mitogen Activated Protein Kinase (MAPK) pathways is evolutionarily highly conserved. Many cells use these pathways to interpret changes to their environment and respond accordingly. The pathways are central to triggering diverse cellular responses such as survival, apoptosis, differentiation and proliferation. Though the interactions between the different MAPK pathways are complex, nevertheless, they maintain a high level of fidelity and specificity to the original signal. There are numerous theories explaining how fidelity and specificity arise within this complex context; spatio-temporal regulation of the pathways and feedback loops are thought to be very important. This paper presents an agent based computational model addressing multi-compartmentalisation and how this influences the dynamics of MAPK cascade activation. The model suggests that multi-compartmentalisation coupled with periodic MAPK kinase (MAPKK) activation may be critical factors for the emergence of oscillation and ultrasensitivity in the system. Finally, the model also establishes a link between the spatial arrangements of the cascade components and temporal activation mechanisms, and how both contribute to fidelity and specificity of MAPK mediated signalling. [ABSTRACT FROM AUTHOR]

Blood-mediated nanoparticle delivery is a new and growing field in the development of therapeutics and diagnostics. Nanoparticle properties such as size, shape and surface chemistry can be controlled to improve their performance in biological systems. This enables modulation of immune system interactions, blood clearance profile and interaction with target cells, thereby aiding effective delivery of cargo within cells or tissues. Their ability to target and enter tissues from the blood is highly dependent on their behaviour under blood flow. Here we have produced an agent-based model of nanoparticle behaviour under blood flow in capillaries. We demonstrate that red blood cells are highly important for effective nanoparticle distribution within capillaries. Furthermore, we use this model to demonstrate how nanoparticle size can selectively target tumour tissue over normal tissue. We demonstrate that the polydispersity of nanoparticle populations is an important consideration in achieving optimal specificity and to avoid off-target effects. In future this model could be used for informing new nanoparticle design and to predict general and specific uptake properties under blood flow. [ABSTRACT FROM AUTHOR]

In the presence of oxygen (O2) the model bacterium Escherichia coli is able to conserve energy by aerobic respiration. Two major terminal oxidases are involved in this process - Cyo has a relatively low affinity for O2 but is able to pump protons and hence is energetically efficient; Cyd has a high affinity for O2 but does not pump protons. When E. coli encounters environments with different O2 availabilities, the expression of the genes encoding the alternative terminal oxidases, the cydAB and cyoABCDE operons, are regulated by two O2-responsive transcription factors, ArcA (an indirect O2 sensor) and FNR (a direct O2 sensor). It has been suggested that O2-consumption by the terminal oxidases located at the cytoplasmic membrane significantly affects the activities of ArcA and FNR in the bacterial nucleoid. In this study, an agent-based modeling approach has been taken to spatially simulate the uptake and consumption of O2 by E. coli and the consequent modulation of ArcA and FNR activities based on experimental data obtained from highly controlled chemostat cultures. The molecules of O2, transcription factors and terminal oxidases are treated as individual agents and their behaviors and interactions are imitated in a simulated 3-D E. coli cell. The model implies that there are two barriers that dampen the response of FNR to O2, i.e. consumption of O2 at the membrane by the terminal oxidases and reaction of O2 with cytoplasmic FNR. Analysis of FNR variants suggested that the monomer-dimer transition is the key step in FNR-mediated repression of gene expression. [ABSTRACT FROM AUTHOR]

The article presents a study that explores the challenges and opportunities brought by the tuberculosis outbreak investigation in southern Mississippi in 2005-2007. It describes the potential sources of disease transmission and epidemiologic links in the outbreak to prevent future transmission in the community. The study suggests that tuberculosis transmission can be prevented by enhanced coordination with substance abuse program, community education, and increasing of outreach capacity.

Abstract: Activation of the transcription factor NF-κB is central to control of immune and inflammatory responses. Cytokine induced activation through the classical or canonical pathway relies on degradation of the inhibitor, IκBα and regulation by the IKKβ kinase. In addition, the NF-κB is activated through the NF-κB-inducing kinase, NIK. Analysis of the IKK/NIK inter-relationship and its impact on NF-κB control, were analysed by mathematical modelling, using matrix formalism and stoichiometrically balanced reactions. The analysis considered a range of bio-reactions and core metabolites and their role in relation to kinase activation and in control of specific steps of the NF-κB pathway. The model predicts a growth-rate and time-dependent transfer of the primary kinase activity from IKKβ to NIK. In addition, it suggests that NIK/IKKβ interdependence is controlled by intermediates of phosphoribosylpyrophosphate (PRPP) within the glycolysis pathway, and thus, identifies a link between specific metabolic events and kinase activation in inflammatory signal transduction. Subsequent in vitro experiments, carried out to validate the impact of IKK/NIK interdependence, confirmed signal amplification at the level of the NF-κB/IκBα complex control in the presence of both kinases. Further, they demonstrate that the induced potentiation is due to synergistic enhancement of relA-dependent activation. [Copyright &y& Elsevier]

Transforming Growth Factor (TGF-β1) is a member of the TGF-beta superfamily ligand-receptor network. and plays a crucial role in tissue regeneration. The extensive in vitro and in vivo experimental literature describing its actions nevertheless describe an apparent paradox in that during re-epithelialisation it acts as proliferation inhibitor for keratinocytes. The majority of biological models focus on certain aspects of TGF-β1 behaviour and no one model provides a comprehensive story of this regulatory factor's action. Accordingly our aim was to develop a computational model to act as a complementary approach to improve our understanding of TGF-β1. In our previous study, an agent-based model of keratinocyte colony formation in 2D culture was developed. In this study this model was extensively developed into a three dimensional multiscale model of the human epidermis which is comprised of three interacting and integrated layers: (1) an agent-based model which captures the biological rules governing the cells in the human epidermis at the cellular level and includes the rules for injury induced emergent behaviours, (2) a COmplex PAthway SImulator (COPASI) model which simulates the expression and signalling of TGF-β1 at the sub-cellular level and (3) a mechanical layer embodied by a numerical physical solver responsible for resolving the forces exerted between cells at the multi-cellular level. The integrated model was initially validated by using it to grow a piece of virtual epidermis in 3D and comparing the in virtuo simulations of keratinocyte behaviour and of TGF-β1 signalling with the extensive research literature describing this key regulatory protein. This research reinforces the idea that computational modelling can be an effective additional tool to aid our understanding of complex systems. In the accompanying paper the model is used to explore hypotheses of the functions of TGF-β1 at the cellular and subcellular level on different keratinocyte populations during epidermal wound healing. [ABSTRACT FROM AUTHOR]

Forager ants lay attractive trail pheromones to guide nestmates to food, but the effectiveness of foraging networks might be improved if pheromones could also be used to repel foragers from unrewarding routes. Here we present empirical evidence for such a negative trail pheromone, deployed by Pharaoh's ants (Monomorium pharaonis) as a ‘no entry’ signal to mark an unrewarding foraging path. This finding constitutes another example of the sophisticated control mechanisms used in self-organized ant colonies. [ABSTRACT FROM AUTHOR]

In vivo and in vitro studies give a paradoxical picture of the actions of the key regulatory factor TGF-β1 in epidermal wound healing with it stimulating migration of keratinocytes but also inhibiting their proliferation. To try to reconcile these into an easily visualized 3D model of wound healing amenable for experimentation by cell biologists, a multiscale model of the formation of a 3D skin epithelium was established with TGF-β1 literature-derived rule sets and equations embedded within it. At the cellular level, an agent-based bottom-up model that focuses on individual interacting units (keratinocytes) was used. This was based on literature-derived rules governing keratinocyte behavior and keratinocyte/ECM interactions. The selection of these rule sets is described in detail in this paper. The agent-based model was then linked with a subcellular model of TGF-β1 production and its action on keratinocytes simulated with a complex pathway simulator. This multiscale model can be run at a cellular level only or at a combined cellular/subcellular level. It was then initially challenged (by wounding) to investigate the behavior of keratinocytes in wound healing at the cellular level. To investigate the possible actions of TGF-β1, several hypotheses were then explored by deliberately manipulating some of these rule sets at subcellular levels. This exercise readily eliminated some hypotheses and identified a sequence of spatial-temporal actions of TGF-β1 for normal successful wound healing in an easy-to-follow 3D model. We suggest this multiscale model offers a valuable, easy-to-visualize aid to our understanding of the actions of this key regulator in wound healing, and provides a model that can now be used to explore pathologies of wound healing. [ABSTRACT FROM AUTHOR]

Abstract: Simulation software is often a fundamental component in systems biology projects and provides a key aspect of the integration of experimental and analytical techniques in the search for greater understanding and prediction of biology at the systems level. It is important that the modelling and analysis software is reliable and that techniques exist for automating the analysis of the vast amounts of data which such simulation environments generate. A rigorous approach to the development of complex modelling software is needed. Such a framework is presented here together with techniques for the automated analysis of such models and a process for the automatic discovery of biological phenomena from large simulation data sets. Illustrations are taken from a major systems biology research project involving the in vitro investigation, modelling and simulation of epithelial tissue. [Copyright &y& Elsevier]

Abstract: We have previously developed Epitheliome, a software agent representation of the growth and repair characteristics of epithelial cell populations, where cell behaviour is governed by a number of simple rules. In this paper, we describe how this model has been extended to incorporate an example of a molecular ‘mechanism’ behind a rule—in this case, how signalling by both endogenous and exogenous ligands of the epidermal growth factor receptor (EGFR) can impact on the proliferation of cell agents. We have developed a mathematical model representing release of endogenous ligand by cells, three-dimensional diffusion of the secreted molecules through a volume of cell culture medium, ligand–receptor binding, and bound receptor internalization and trafficking. Information relating to quantities of molecular species associated with each cell agent is frequently exchanged between the agent and signalling models, and the ratio of bound to free receptors determines cell cycle progression and hence the proliferative behaviour of the cell agents. We have applied this integrated model to examine the effect of plating density on tissue growth via autocrine/paracrine signalling. This predicts that cell growth is dependent on the concentration of exogenous ligand, but where this is limited, then growth becomes dependent on cell density and the availability of endogenous ligand. We have further modified the calcium concentration of the medium to modulate the formation of intercellular bonds between cells and shown that the increased propensity for cells to form colonies in physiological calcium does not result in significantly different patterns of receptor occupancy. In conclusion, our approach demonstrates that by combining agent-based and mathematical modelling paradigms, it is possible to probe the complex feedback relationship between the behaviour of individual cells and their interaction with one another and their environment. [Copyright &y& Elsevier]

Abstract: Individual-based or agent-based models have proved useful in a variety of different biological contexts. This paper presents an agent-based model using a formal computational modelling approach to model a crucial biological system—the intracellular NF-κB signalling pathway. The pathway is vital to immune response regulation, and is fundamental to basic survival in a range of species. Alterations in pathway regulation underlie many diseases, including atherosclerosis and arthritis. Our modelling of individual molecules, receptors and genes provides a more comprehensive outline of regulatory network mechanisms than previously possible with equation-based approaches. The model has been validated with data obtained from single cell experimental analysis. [Copyright &y& Elsevier]

Demonstrates how the P systems with replicated rewriting can be modeled by X-machines also called Eilenberg machines. Definition of a P system; Computation for simulating P systems; Complexity aspects of P systems.