Computational Methods in Systems Biology
About: Computational Methods in Systems Biology is an academic conference. The conference publishes majorly in the area(s): Model checking & Petri net. Over the lifetime, 467 publications have been published by the conference receiving 9229 citations.
Papers published on a yearly basis
••28 Sep 2004
TL;DR: A finer-grained concurrent model, the mK-calculus, is considered, where interactions have to be at most binary, and it is shown how to embed the coarser- grained language in the latter, a properly which the authors call self-assembly.
Abstract: A language of formal proteins, the K-calculus, is introduced. Interactions are modeled at the domain level, bonds are represented by means of shared names, and reactions are required to satisfy a causality requirement of monotonicity.An example of a simplified signalling pathway is introduced to illustrate how standard biological events can be expressed in our protein language. A more comprehensive example, the lactose operon, is also developed, bringing some confidence in the formalism considered as a modeling language.Then a finer-grained concurrent model, the mK-calculus, is considered, where interactions have to be at most binary. We show how to embed the coarser-grained language in the latter, a properly which we call self-assembly.Finally we show how the finer-grained language can itself be encoded in π-calculus, a standard foundational language for concurrency theory.
28 Sep 2004
TL;DR: This work presents the BioAmbients calculus, which is suitable for representing various aspects of molecular localization and compartmentalization, including the movement of molecules between compartments, the dynamic rearrangement of cellularcompartments, and the interaction between molecules in a compartmentalized setting.
Abstract: Biomolecular systems, composed of networks of proteins, underlie the major functions of living cells. Compartments are key to the organization of such systems. We have previously developed an abstraction for biomolecular systems using the π-calculus process algebra, which successfully handled their molecular and biochemical aspects, but provided only a limited solution for representing compartments. In this work, we extend this abstraction to handle compartments. We are motivated by the ambient calculus, a process algebra for the specification of process location and movement through computational domains. We present the BioAmbients calculus, which is suitable for representing various aspects of molecular localization and compartmentalization, including the movement of molecules between compartments, the dynamic rearrangement of cellular compartments, and the interaction between molecules in a compartmentalized setting. Guided by the calculus, we adapt the BioSpi simulation system, to provide an extended modular framework for molecular and cellular compartmentalization, and we use it to model and study a complex multi-cellular system.
26 May 2004
TL;DR: This work introduces a family of process calculi with dynamic nested membranes that are tightly coupled to membranes, and can perform interactions on both sides of a membrane.
Abstract: We introduce a family of process calculi with dynamic nested membranes. In contrast to related calculi, including some developed for biological applications, active entities here are tightly coupled to membranes, and can perform interactions on both sides of a membrane. That is, computation happens on the membrane, not inside of it.
••12 Oct 2008
TL;DR: The continuous π-calculus, a process algebra for modelling behaviour and variation in molecular systems, is introduced and its expressive succinctness and support for diverse interaction between agents via a flexible network of molecular affinities are discussed.
Abstract: We introduce the continuous π-calculus, a process algebra for modelling behaviour and variation in molecular systems. Key features of the language are: its expressive succinctness; support for diverse interaction between agents via a flexible network of molecular affinities; and operational semantics for a continuous space of processes. This compositional semantics also gives a modular way to generate conventional differential equations for system behaviour over time. We illustrate these features with a model of an existing biological system, a simple oscillatory pathway in cyanobacteria. We then discuss future research directions, in particular routes to applying the calculus in the study of evolutionary properties of biochemical pathways.
••27 Aug 2009
TL;DR: This work presents the first algorithm for performing statistical Model Checking using Bayesian Sequential Hypothesis Testing, and shows that this Bayesian approach outperforms current statistical Model checking techniques, which rely on tests from Classical statistics, by requiring fewer system simulations.
Abstract: Recently, there has been considerable interest in the use of Model Checking for Systems Biology. Unfortunately, the state space of stochastic biological models is often too large for classical Model Checking techniques. For these models, a statistical approach to Model Checking has been shown to be an effective alternative. Extending our earlier work, we present the first algorithm for performing statistical Model Checking using Bayesian Sequential Hypothesis Testing. We show that our Bayesian approach outperforms current statistical Model Checking techniques, which rely on tests from Classical (aka Frequentist) statistics, by requiring fewer system simulations. Another advantage of our approach is the ability to incorporate prior Biological knowledge about the model being verified. We demonstrate our algorithm on a variety of models from the Systems Biology literature and show that it enables faster verification than state-of-the-art techniques, even when no prior knowledge is available.