Computational modeling of biological systems is becoming increasingly important in efforts to better understand complex biological behaviors. In this review, we distinguish between two types of biological models--mathematical and computational--which differ in their representations of biological phenomena. We call the approach of constructing computational models of biological systems 'executable biology', as it focuses on the design of executable computer algorithms that mimic biological phenomena. We survey the main modeling efforts in this direction, emphasize the applicability and benefits of executable models in biological research and highlight some of the challenges that executable biology poses for biology and computer science. We claim that for executable biology to reach its full potential as a mainstream biological technique, formal and algorithmic approaches must be integrated into biological research. This will drive biology toward a more precise engineering discipline.

/pdf/executable-cell-biology-cjdtb2p8cz.pdf

Executable cell biology.

Mathematical modelling is increasingly used to get insights into the functioning of complex biological networks. In this context, Petri nets (PNs) have recently emerged as a promising tool among the various methods employed for the modelling and analysis of molecular networks. PNs come with a series of extensions, which allow different abstraction levels, from purely qualitative to more complex quantitative models. Noteworthily, each of these models preserves the underlying graph, which depicts the interactions between the biological components. This article intends to present the basics of the approach and to foster the potential role PNs could play in the development of the computational systems biology.

http://chess.eecs.berkeley.edu/design/2009/discussion/Pdf/PN_bio_networks.pdf

Petri net modelling of biological networks

Apoptosis is regulated by several signaling pathways which are extensively linked by crosstalks. Boolean or logical modeling has become a promising approach to capture the qualitative behavior of such complex networks. Here we built a largescale literature-based Boolean model of the central intrinsic and extrinsic apoptosis pathways as well as pathways connected with them. The model responds to several external stimuli such as Fas ligand, TNF-a, UV-B irradiation, interleukin1b and insulin. Timescales and multi-value node logic were used and turned out to be indispensable to reproduce the behavior of the apoptotic network. The coherence of the model was experimentally validated. Thereby an UV-B dose-effect is shown for the first time in mouse hepatocytes. Analysis of the model revealed a tight regulation emerging from high connectivity and spanning crosstalks and a particular importance of feedback loops. An unexpected feedback from Smac release to RIP could further increase complex II formation. The introduced Boolean model provides a comprehensive and coherent description of the apoptosis network behavior. It gives new insights into the complex interplay of pro- and antiapoptotic factors and can be easily expanded to other signaling pathways.

/pdf/on-off-and-beyond-a-boolean-model-of-apoptosis-200qa48fuf.pdf

ON/OFF and Beyond - A Boolean Model of Apoptosis

Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future.

/pdf/modeling-formalisms-in-systems-biology-2bu1tjfky4.pdf

Modeling formalisms in Systems Biology

A ubiquitous building block of signaling pathways is a cycle of covalent modification (e.g., phosphorylation and dephosphorylation in MAPK cascades). Our paper explores the kind of information processing and filtering that can be accomplished by this simple biochemical circuit. Signaling cycles are particularly known for exhibiting a highly sigmoidal (ultrasensitive) input–output characteristic in a certain steady-state regime. Here, we systematically study the cycle's steady-state behavior and its response to time-varying stimuli. We demonstrate that the cycle can actually operate in four different regimes, each with its specific input–output characteristics. These results are obtained using the total quasi–steady-state approximation, which is more generally valid than the typically used Michaelis-Menten approximation for enzymatic reactions. We invoke experimental data that suggest the possibility of signaling cycles operating in one of the new regimes. We then consider the cycle's dynamic behavior, which has so far been relatively neglected. We demonstrate that the intrinsic architecture of the cycles makes them act—in all four regimes—as tunable low-pass filters, filtering out high-frequency fluctuations or noise in signals and environmental cues. Moreover, the cutoff frequency can be adjusted by the cell. Numerical simulations show that our analytical results hold well even for noise of large amplitude. We suggest that noise filtering and tunability make signaling cycles versatile components of more elaborate cell-signaling pathways.

/pdf/operating-regimes-of-signaling-cycles-statics-dynamics-and-45yq6w2ck6.pdf

Operating Regimes of Signaling Cycles: Statics, Dynamics, and Noise Filtering

This paper first presents basic Petri net components representing molecular interactions and mechanisms of signalling pathways, and introduces a method to construct a Petri net model of a signalling pathway with these components. Then a simulation method of determining the delay time of transitions, by using timed Petri nets — i.e. the time taken in firing of each transition — is proposed based on some simple principles that the number of tokens flowed into a place is equivalent to the number of tokens flowed out. Finally, the availability of proposed method is confirmed by observing signalling transductions in biological pathways through simulation experiments of the apoptosis signalling pathways as an example.

Modelling and simulation of signal transductions in an apoptosis pathway by using timed Petri nets.

The purpose of this paper is to discuss how to model and analyze signaling pathways by using Petri net. Firstly, we propose a modeling method based on Petri net by paying attention to the molecular interactions and mechanisms. Then, we introduce a new notion "activation transduction component" in order to describe an enzymic activation process of reactions in signaling pathways and shows its correspondence to a so-called elementary T-invariant in the Petri net models. Further, we design an algorithm to effectively find basic enzymic activation processes by obtaining a series of elementary T-invariants in the Petri net models. Finally, we demonstrate how our method is practically used in modeling and analyzing signaling pathway mediated by thrombopoietin as an example.

Structural modeling and analysis of signaling pathways based on Petri nets.

This chapter gives an introduction of Petri nets, its applications and security challenges. Petri nets are a graphical and mathematical modeling tool available to many systems. Once a system is modeled as a Petri net, the behavior of the system can be simulated by using tokens on the Petri net. Petri nets’ abundant techniques can be used to solve many problems associated with the modeled system. This chapter gives formal definitions, properties and analysis methods of Petri nets, and gives several examples to illustrate some basic concepts and successful application areas of Petri nets. Then this chapter presents Petri nets based challenges to security such as Intrusion Detection System, security policy design and analysis, and cryptography tool.

Introduction of Petri Nets: Its Applications and Security Challenges

This paper deals with WF-net based modeling and verification of interorganizational workflows (interworkflows for short) based on the protocol of WfMC. In the protocol, there are three patterns of interoperability: Chained, Nested, and Parallel synchronized; and an interworkflow is constructed by using those interoperability patterns. We first give a WF-net based modeling method. In this modeling method, the three interoperability patterns are respectively expressed in terms of WF-nets. They enable us to model a given interworkflow as a WF-net by connecting WF-nets representing its constituent workflows. We also indicate that if free choice WF-nets are connected by means of any combination of the three patterns then the resultant WF-net is asymmetric choice. Next we discuss verification of WF-nets obtained through the modeling method. Intuitively, a WF-net is said to be sound if, for any case, the initial state is always transformed to the final state. Unfortunately, even if every constituent WF-net is sound FC, the resultant WF-net is not always sound. We give a sufficient condition of non-soundness checkable in polynomial time. We also show that if they are connected by only the Nested pattern then the resultant WF-net is sound.

Qi-Wei Ge

Papers

Modelling and simulation of signal transductions in an apoptosis pathway by using timed Petri nets.

Structural modeling and analysis of signaling pathways based on Petri nets.

Introduction of Petri Nets: Its Applications and Security Challenges

WF-Net Based Modeling and Soundness Verification of Interworkflows

A Proposal of a Flexible and Efficient Workflow Change Type