Ontology based standardization of Petri net modeling for signaling pathways

Taking account of the great availability of Petri nets in modeling and analyzing large complicated signaling networks, semantics of Petri nets is in need of systematization for the purpose of consistency and reusability of the models. This paper reports on standardization of units of Petri nets on the basis of an ontology that gives an intrinsic definition to the process of signaling in signaling pathways.     

Modular synthesis of Petri nets for modeling flexible manufacturing systems

This paper proposes a modular Petri net synthesis method for modeling flexible manufacturing systems based on synchronization among control processes of the manufacturing resources (such as robots and machines). In the method, the target system is modeled in a bottom-up and uniform manner by first describing the system's control processes using strongly connected state machines (SCSMs) as the basic modules. Each SCSM may contain multiple tokens to represent resources from the same type such as spaces in a buffer. Next, the common transitions and common transition subnets of the modules are merged to represent their synchronization. The system model constructed is proven to be conservative and thus bounded. Moreover, a restricted class of merged nets is proven to be live and reversible. For general classes of merged nets, this paper shows theorems that easily calculateP-invariants of the final net without solving the linear system equations. TheseP-invariants can be used to help in verifying the model's qualitative properties such as liveness.     

Quantitative Petri net model of gene regulated metabolic networks in the cell

A method to exploit hybrid Petri nets (HPN) for quantitatively modeling and simulating gene regulated metabolic networks is demonstrated. A global kinetic modeling strategy and Petri net modeling algorithm are applied to perform the bioprocess functioning and model analysis. With the model, the interrelations between pathway analysis and metabolic control mechanism are outlined. Diagrammatical results of the dynamics of metabolites are simulated and observed by implementing a HPN tool, Visual Object Net ++. An explanation of the observed behavior of the urea cycle is proposed to indicate possibilities for metabolic engineering and medical care. Finally, the perspective of Petri nets on modeling and simulation of metabolic networks is discussed.     

Model validation of biological pathways using Petri nets--demonstrated for apoptosis

This paper demonstrates the first steps of a new integrating methodology to develop and analyse models of biological pathways in a systematic manner using well established Petri net technologies. The whole approach comprises step-wise modelling, animation, model validation as well as qualitative and quantitative analysis for behaviour prediction. In this paper, the first phase is addressed how to develop and validate a qualitative model, which might be extended afterwards to a quantitative model. The example used in this paper is devoted to apoptosis, the genetically programmed cell death. Apoptosis is an essential part of normal physiology for most metazoan species. Disturbances in the apoptotic process could lead to several diseases. The signal transduction pathway of apoptosis includes highly complex mechanisms to control and execute programmed cell death. This paper explains how to model and validate this pathway using qualitative Petri nets. The results provide a mathematically unique and valid model enabling the confirmation of known properties as well as new insights in this pathway.     

Algebraic properties of automata associated to Petri nets and applications to computation in biological systems

Biochemical and genetic regulatory networks are often modeled by Petri nets. We study the algebraic structure of the computations carried out by Petri nets from the viewpoint of algebraic automata theory. Petri nets comprise a formalized graphical modeling language, often used to describe computation occurring within biochemical and genetic regulatory networks, but the semantics may be interpreted in different ways in the realm of automata. Therefore, there are several different ways to turn a Petri net into a state-transition automaton. Here, we systematically investigate different conversion methods and describe cases where they may yield radically different algebraic structures. We focus on the existence of group components of the corresponding transformation semigroups, as these reflect symmetries of the computation occurring within the biological system under study. Results are illustrated by applications to the Petri net modelling of intermediary metabolism. Petri nets with inhibition are shown to be computationally rich, regardless of the particular interpretation method. Along these lines we provide a mathematical argument suggesting a reason for the apparent all-pervasiveness of inhibitory connections in living systems.     

Modeling FMS with decision Petri nets

Decision point extended timed Petri nets or decision Petri nets (DPN) are introduced as an extended modeling framework for FMS performance evaluation. The decision point extension allows the explicit modeling of the control of the flow of tokens in timed Petri nets and hence represents the control of the flow of material, resources, and information in FMS. Further, the concept of a bounded transition is proposed to conveniently model the blocking logic in an FMS with limited buffer capacities. The motivation to present these conventions is to develop a user-friendly graphic model to represent FMS designs for analysis by discrete event simulation. DPN affords concise models that can be conveniently developed and easily transformed into discrete event simulation models. With the help of a simple FMS example, which includes a number of part types, loading rules, dispatching rules, and probabilistic branching (at an inspection station), we illustrate the DPN model development. As an illustration of the ease with which it can be tranformed into a simulation model, we have developed a generalized simulator called ROBSIM and outline here its methodological basis. The proposed concepts should be of interest to users of discrete event simulation in FMS design or elsewhere to tap the potential of basic Petri net concepts for graphic representation and specification purposes. In particular, our work should encourage other researchers to develop extensions relevant to their own areas of interest.     

Colored Petri net modeling and simulation of signal transduction pathways

Presented herein is a methodology for quantitatively analyzing the complex signaling network by resorting to colored Petri nets (CPN). The mathematical as well as Petri net models for two basic reaction types were established, followed by the extension to a large signal transduction system stimulated by epidermal growth factor (EGF) in an application study. The CPN models based on the Petri net representation and the conservation and kinetic equations were used to examine the dynamic behavior of the EGF signaling pathway. The usefulness of Petri nets is demonstrated for the quantitative analysis of the signal transduction pathway. Moreover, the trade-offs between modeling capability and simulation efficiency of this pathway are explored, suggesting that the Petri net model can be invaluable in the initial stage of building a dynamic model.     

Maintenance Integration in Manufacturing Systems: From the Modeling Tool to Evaluation

In manufacturing systems, wear-out and eventual failure are unavoidable. However, to reduce the rate of their occurrence and to prolong the life of equipment or the capacity for extended productive use of the equipment under the necessary technological functioning and servicing, maintenance can be performed. For large manufacturing systems, maintenance integration involves a particular development concerned with both complexity models and computing time. This paper presents an effective way of modeling complex manufacturing systems through hierarchical and modular analysis by using stochastic Petri nets and Markov chains. In the proposed approach, the integration of maintenance policies in a manufacturing system is facilitated by the development of a generic model. With this generic modeling, the user doesn't need to code the strategies but only to instantiate the generic model with the structure of the manufacturing system. This method allows various maintenance strategies to be coded in the generic model with the aim of studying their influence on system dependability and performance.     

Constructing biological pathway models with hybrid functional Petri nets

In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofest?dt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.     

Near optimal manufacturing flow controller design

Flow control of flexible manufacturing systems (FMSs) addresses an important real-time scheduling requirement of modern manufacturing facilities, which are prone to failures and other controllable or stochastic discrete events affecting production capacity, such as change of setup and maintenance scheduling. Flow controllers are useful both in the coordination of interconnected flexible manufacturing cells through distributed scheduling policies and in the hierarchical decomposition of the planning and scheduling problem of complex manufacturing systems. Optimal flow-control policies are hedging-point policies characterized by a generally intractable system of stochastic partial differential equations. This article proposes a near optimal controller whose design is computationally feasible for realistic-size systems. The design exploits a decomposition of the multiple-part-type problem to many analytically tractable one-part-type problems. The decomposition is achieved by replacing the polyhedra production capacity sets with inscribed hypercubes. Stationary marginal densities of state variables are computed iteratively for successive trial controller designs until the best inscribed hypercubes and the associated optimal hedging points are determined. Computational results are presented for an illustrative example of a failureprone FMS.     

基于Petri网T不变量的PHB新陈代谢建模分析(英文)

从拓扑结构的角度分析生化反应网络是生物信息学研究中的一个热点问题。通过将两种传统的途径分析方法(基元模式和极端途径)与Petri网的T不变量分析进行了比较,结果表明:它们本质上是一致的,但是采用Petri网的T不变量分析更便捷。然后,利用Petri网技术构建了PHB代谢模型。对该模型作了结构分析,将计算得到的23个T不变量进行了分组:I组表示简单的可逆反应,II组表示循环的反应,III组可用于调控ATP/ADP比率,IV组是与PHB生产直接相关的反应,可用于代谢工程以提高PHB的产率。最后讨论了Petri网的T不变量分析在这个领域中的应用。     

An architecture for a shop-floor controller using colored Petri nets

In a dynamic and flexible manufacturing environment, a shop-floor controller must be designed so that it automatically (or with minimum human intervention) and quickly responds to the changes (e.g., in part type or part routing) in the system. Such a performance may be achieved provided that the controller is simple and sufficiently general in its scope of application. In this article, we present an architecture for such a shop-floor controller. The architecture is based on colored Petri nets with ordered colored sets and structured input and output functions.     

Developing manufacturing control software: A survey and critique

The complexity and diversity of manufacturing software and the need to adapt this software to the frequent changes in the production requirements necessitate the use of a systematic approach to developing this software. The software life-cycle model (Royce, 1970) that consists of specifying the requirements of a software system, designing, implementing, testing, and evolving this software can be followed when developing large portions of manufacturing software. However, the presence of hardware devices in these systems and the high costs of acquiring and operating hardware devices further complicate the manufacturing software development process and require that the functionality of this software be extended to incorporate simulation and prototyping. This paper reviews recent methods for planning, scheduling, simulating, and monitoring the operation of manufacturing systems. A synopsis of the approaches to designing and implementing the real-time control software of these systems is presented. It is concluded that current methodologies support, in a very restricted sense, these planning, scheduling, and monitoring activities, and that enhanced performance can be achieved via an integrated approach.     

Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models

Background

Network inference methods reconstruct mathematical models of molecular or genetic networks directly from experimental data sets. We have previously reported a mathematical method which is exclusively data-driven, does not involve any heuristic decisions within the reconstruction process, and deliveres all possible alternative minimal networks in terms of simple place/transition Petri nets that are consistent with a given discrete time series data set.

Results

We fundamentally extended the previously published algorithm to consider catalysis and inhibition of the reactions that occur in the underlying network. The results of the reconstruction algorithm are encoded in the form of an extended Petri net involving control arcs. This allows the consideration of processes involving mass flow and/or regulatory interactions. As a non-trivial test case, the phosphate regulatory network of enterobacteria was reconstructed using in silico-generated time-series data sets on wild-type and in silico mutants.

Conclusions

The new exact algorithm reconstructs extended Petri nets from time series data sets by finding all alternative minimal networks that are consistent with the data. It suggested alternative molecular mechanisms for certain reactions in the network. The algorithm is useful to combine data from wild-type and mutant cells and may potentially integrate physiological, biochemical, pharmacological, and genetic data in the form of a single model.     

Real-time software methodologies: Are they suitable for developing Manufacturing control software?

Computer-Integrated Manufacturing (CIM) systems may be classified as real-time systems. Hence, the applicability of methodologies that are developed for specifying, designing, implementing, testing, and evolving real-time software is investigated in this article. The paper highlights the activities of the software development process. Among these activities, a great emphasis is placed on automating the software requirements specification activity, and a set of formal models and languages for specifying these requirements is presented. Moreover, a synopsis of the real-time software methodologies that have been implemented by the academic and industrial communities is presented together with a critique of the strengths and weaknesses of these methodologies. The possible use of the real-time methodologies in developing the control software of efficient and dependable manufacturing systems is explored. In these systems, efficiency is achieved by increasing the level of concurrency of the operations of a plan, and by scheduling the execution of these operations with the intent of maximizing the utilization of the devices of their systems. On the other hand, dependability requires monitoring the operations of these systems. This monitoring activity facilitates the detection of faults that may occur when executing the scheduled operations of a plan, recovering from these faults, and, whenever feasible, resuming the original schedule of the system. The paper concludes that the set of surveyed methodologies may be used to develop the real-time control software of efficient and dependable manufacturing systems. However, an integrated approach to planning, scheduling, and monitoring the operations of these systems will significantly enhance their utility, and no such approach is supported by any of these methodologies.     

Modeling and simulation of molecular biology systems using petri nets: modeling goals of various approaches

Petri nets are a discrete event simulation approach developed for system representation, in particular for their concurrency and synchronization properties. Various extensions to the original theory of Petri nets have been used for modeling molecular biology systems and metabolic networks. These extensions are stochastic, colored, hybrid and functional. This paper carries out an initial review of the various modeling approaches based on Petri net found in the literature, and of the biological systems that have been successfully modeled with these approaches. Moreover, the modeling goals and possibilities of qualitative analysis and system simulation of each approach are discussed.     

RFID-enhanced multi-agent based control for a machining system

Recent research on highly distributed control methods for complex systems have produced a series of philosophies based on negotiation, that bring together process engineering with computer science. Among these control philosophies, the ones based on multi-agent systems (MAS) have become especially relevant. Furthermore, among a number of MAS implementations, those that use different types of agents at different conceptual/managerial levels are commonly applied. However, these MAS models have the drawback of an excessive dependence on up-to-date information about the products and other elements that move within the system. A new technology has come out that can help solve this problem: radio-frequency identification enhanced information management systems (RFID-IMS). One of these is Auto-ID/EPCglobal technology. This paper shows how a MAS model can be used for controlling a machining system incorporating RFID-IMS technology. The resulting system becomes an RFID-enhanced intelligent manufacturing system (RFID-IMS II).     

Self-reproducing systems: structure, niche relations and evolution.

A formal definition of a self-reproducing system is proposed using Petri nets. A potential self-reproducing system is a set of places in the Petri net such that the number of tokens in each place increases due to some sequence of internal transitions (a transition is called internal to the marked subset of places if at least one of its starting places and one of its terminating places belongs to that subset). An actual self-reproducing system is a system that compensates the outflow of its components by reproduction. In a suitable environment every potential self-reproducing system becomes an actual one. Each Petri net can be considered as an ecosystem with the web of ecological niches bound together with trophic and other relations. The stationary dynamics of the ecosystem is characterized by the set of filled niches. The process of evolution is described in terms of niche composition change. Perspectives of the theory of self-reproducing systems in biology are discussed.     

Towards an Integration of Process Planning and Production Planning and Control for Flexible Manufacturing Systems

This introduction article attempts to present some major issues relating to the integration of process planning and production planning and control (PPC) for flexible manufacturing systems (FMSs). It shows that the performance of an FMS can be significantly improved and FMS capabilities more effectively utilized by integrating process planning and PPC functions. The various types of flexibility to be planned and provided for in process planning and manufacturing are summarized in the article, as well as emerging conceptual frameworks for integration, along with their implementation requirements and problems. Distinctive elements that differentiate these frameworks, such as the extent of integration of process planning and PPC activities, number of alternative process plans, and the time at which numerical control programs are generated, are discussed, followed by a brief summary of the articles compiled for this special issue.     

A structured approach for the engineering of biochemical network models, illustrated for signalling pathways

Quantitative models of biochemical networks (signal transduction cascades, metabolic pathways, gene regulatory circuits) are a central component of modern systems biology. Building and managing these complex models is a major challenge that can benefit from the application of formal methods adopted from theoretical computing science. Here we provide a general introduction to the field of formal modelling, which emphasizes the intuitive biochemical basis of the modelling process, but is also accessible for an audience with a background in computing science and/or model engineering. We show how signal transduction cascades can be modelled in a modular fashion, using both a qualitative approach--qualitative Petri nets, and quantitative approaches--continuous Petri nets and ordinary differential equations (ODEs). We review the major elementary building blocks of a cellular signalling model, discuss which critical design decisions have to be made during model building, and present a number of novel computational tools that can help to explore alternative modular models in an easy and intuitive manner. These tools, which are based on Petri net theory, offer convenient ways of composing hierarchical ODE models, and permit a qualitative analysis of their behaviour. We illustrate the central concepts using signal transduction as our main example. The ultimate aim is to introduce a general approach that provides the foundations for a structured formal engineering of large-scale models of biochemical networks.