Enhanced Operational Semantics in Systems Biology

We are faced with a great challenge: the cross-fertilization between the fields of formal methods for concurrency, in the computer science domain, and systems biology in the biological realm

Flux Analysis in Process Models via Causality

We present an approach for flux analysis in process algebra models of biological systems. We perceive flux as the flow of resources in stochastic simulations. We resort to an established correspondence between event structures, a broadly recognised model of concurrency, and state transitions of process models, seen as Petri nets. We show that we can this way extract the causal resource dependencies in simulations between individual state transitions as partial orders of events. We propose transformations on the partial orders that provide means for further analysis, and introduce a software tool, which implements these ideas. By means of an example of a published model of the Rho GTP-binding proteins, we argue that this approach can provide the substitute for flux analysis techniques on ordinary differential equation models within the stochastic setting of process algebras

Performance and cryptographic evaluation of security protocols in distributed networks using applied pi calculus and Markov Chain

The development of cryptographic protocols goes through two stages, namely, security verification and performance analysis. The verification of the protocol’s security properties could be analytically achieved using threat modelling, or formally using formal methods and model checkers. The performance analysis could be mathematical or simulation-based. However, mathematical modelling is complicated and does not reflect the actual deployment environment of the protocol in the current state of the art. Simulation software provides scalability and can simulate complicated scenarios, however, there are times when it is not possible to use simulations due to a lack of support for new technologies or simulation scenarios. Therefore, this paper proposes a formal method and analytical model for evaluating the performance of security protocols using applied pi-calculus and Markov Chain processes. It interprets algebraic processes and associates cryptographic operatives with quantitative measures to estimate and evaluate cryptographic costs. With this approach, the protocols are presented as processes using applied pi-calculus, and their security properties are an approximate abstraction of protocol equivalence based on the verification from ProVerif and evaluated using analytical and simulation models for quantitative measures. The interpretation of the quantities is associated with process transitions, rates, and measures as a cost of using cryptographic primitives. This method supports users’ input in analysing the protocol’s activities and performance. As a proof of concept, we deploy this approach to assess the performance of security protocols designed to protect large-scale, 5G-based Device-to-Device communications. We also conducted a performance evaluation of the protocols based on analytical and network simulator results to compare the effectiveness of the proposed approach

Logical Specification of Operational Semantics

Various logic-based frameworks have been proposed for specifying the operational semantics of programming languages and concurrent systems, including inference systems in the styles advocated byPlotkin and by Kahn, Horn logic, equational specifications, reductionsystems for evaluation contexts, rewriting logic, and tile logic.We consider the relationship between these frameworks, and assess theirrespective merits and drawbacks - especially with regard to the modularity of specifications, which is a crucial feature for scaling up to practicalapplications. We also report on recent work towards the use of the Maudesystem (which provides an efficient implementation of rewriting logic) asa meta-tool for operational semantics

Simulation of non-Markovian Processes in BlenX

BlenX is a programming language explicitly designed for modeling biological processes inspired by Beta-binders. The actual framework assumes biochemical interactions being exponentially distributed, i.e., an underlying Markov process is associated with BlenX programs. In this paper we relax this condition by providing formal tools for managing non-Markovian processes within BlenX

Foundations of Modular SOS

A novel form of labelled transition system is proposed, wherethe labels are the arrows of a category, and adjacent labels in computations are required to be composable. Such transition systems provide thefoundations for modular SOS descriptions of programming languages.Three fundamental ways of transforming label categories, analogous tomonad transformers, are provided, and it is shown that their applicationspreserve computations in modular SOS. The approach is illustrated withfragments taken from a modular SOS for ML concurrency primitives

Design Environments for Complex Systems

The paper describes an approach for modeling complex systems by hiding as much formal details as possible from the user, still allowing verification and simulation of the model. The interface is based on UML to make the environment available to the largest audience. To carry out analysis, verification and simulation we automatically extract process algebras specifications from UML models. The results of the analysis is then reflected back in the UML model by annotating diagrams. The formal model includes stochastic information to handle quantitative parameters. We present here the stochastic -calculus and we discuss the implementation of its probabilistic support that allows simulation of processes. We exploit the benefits of our approach in two applicative domains: global computing and systems biology

Formal executable descriptions of biological systems

The similarities between systems of living entities and systems of concurrent processes may support biological experiments in silico. Process calculi offer a formal framework to describe biological systems, as well as to analyse their behaviour, both from a qualitative and a quantitative point of view. A couple of little examples help us in showing how this can be done. We mainly focus our attention on the qualitative and quantitative aspects of the considered biological systems, and briefly illustrate which kinds of analysis are possible. We use a known stochastic calculus for the first example. We then present some statistics collected by repeatedly running the specification, that turn out to agree with those obtained by experiments in vivo. Our second example motivates a richer calculus. Its stochastic extension requires a non trivial machinery to faithfully reflect the real dynamic behaviour of biological systems

Control Flow Analysis for BioAmbients

AbstractThis paper presents a static analysis for investigating properties of biological systems specified in BioAmbients. We exploit the control flow analysis to decode the bindings of variables induced by communications and to build a relation of the ambients that can interact with each other. We eventually apply our analysis to an example of gene regulation by positive feedback taken from the literature

Control Flow Analysis for BioAmbients

AbstractThis paper presents a static analysis for investigating properties of biological systems specified in BioAmbients. We exploit the control flow analysis to decode the bindings of variables induced by communications and to build a relation of the ambients that can interact with each other. We eventually apply our analysis to an example of gene regulation by positive feedback taken from the literature