BioAmbients: an abstraction for biological compartments
28 Sep 2004-Vol. 325, Iss: 1, pp 141-167
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.
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TL;DR: It is claimed that for executable biology to reach its full potential as a mainstream biological technique, formal and algorithmic approaches must be integrated into biological research, which will drive biology toward a more precise engineering discipline.
Abstract: 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.
568 citations
Cites background from "BioAmbients: an abstraction for bio..."
...Many other studies have followed this direction, including experiments using the ambient calculu...
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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.
550 citations
Cites background from "BioAmbients: an abstraction for bio..."
...Finally we show how the 0ner-grained language can itself be encoded in -calculus, a standard foundational language for concurrency theory. c© 2004 Published by Elsevier B.V....
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TL;DR: Bio-PEPA is a modification of PEPA, originally defined for the performance analysis of computer systems, in order to handle some features of biological models, such as stoichiometry and the use of general kinetic laws.
377 citations
Cites background from "BioAmbients: an abstraction for bio..."
...In recent years there has been increasing interest in the application of process algebras in the modelling and analysis of biological systems [50,26,31,49,16,45,11]....
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...This problem impacts also on other process algebras [50,49,16]....
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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.
371 citations
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.
356 citations
Cites background from "BioAmbients: an abstraction for bio..."
...This led, for example, to the development of the biochemical stochastic π-calculus [1] and BioAmbients [14]....
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References
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TL;DR: The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing.
Abstract: Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
35,225 citations
"BioAmbients: an abstraction for bio..." refers background in this paper
...Despite the critical role of compartments in biology, most existing models of biological systems have focused on chemical reactions and pay little attention to this level of organization....
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TL;DR: In this article, a simulation algorithm for the stochastic formulation of chemical kinetics is proposed, which uses a rigorously derived Monte Carlo procedure to numerically simulate the time evolution of a given chemical system.
Abstract: There are two formalisms for mathematically describing the time behavior of a spatially homogeneous chemical system: The deterministic approach regards the time evolution as a continuous, wholly predictable process which is governed by a set of coupled, ordinary differential equations (the “reaction-rate equations”); the stochastic approach regards the time evolution as a kind of random-walk process which is governed by a single differential-difference equation (the “master equation”). Fairly simple kinetic theory arguments show that the stochastic formulation of chemical kinetics has a firmer physical basis than the deterministic formulation, but unfortunately the stochastic master equation is often mathematically intractable. There is, however, a way to make exact numerical calculations within the framework of the stochastic formulation without having to deal with the master equation directly. It is a relatively simple digital computer algorithm which uses a rigorously derived Monte Carlo procedure to numerically simulate the time evolution of the given chemical system. Like the master equation, this “stochastic simulation algorithm” correctly accounts for the inherent fluctuations and correlations that are necessarily ignored in the deterministic formulation. In addition, unlike most procedures for numerically solving the deterministic reaction-rate equations, this algorithm never approximates infinitesimal time increments df by finite time steps At. The feasibility and utility of the simulation algorithm are demonstrated by applying it to several well-known model chemical systems, including the Lotka model, the Brusselator, and the Oregonator.
10,275 citations
"BioAmbients: an abstraction for bio..." refers background in this paper
...Each ambient harbors a collection of processes, that reside and run directly within it....
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Book•
01 Jan 1986
TL;DR: Molecular cell biology, Molecular cell biology , مرکز فناوری اطلاعات و اصاع رسانی, کδاوρزی
Abstract: Molecular cell biology , Molecular cell biology , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی
6,754 citations
TL;DR: A model is described that delineates the roles of individual hormonal and neuropeptide signalling pathways in the control of food intake and the means by which obesity can arise from inherited or acquired defects in their function.
Abstract: New information regarding neuronal circuits that control food intake and their hormonal regulation has extended our understanding of energy homeostasis, the process whereby energy intake is matched to energy expenditure over time. The profound obesity that results in rodents (and in the rare human case as well) from mutation of key signalling molecules involved in this regulatory system highlights its importance to human health. Although each new signalling pathway discovered in the hypothalamus is a potential target for drug development in the treatment of obesity, the growing number of such signalling molecules indicates that food intake is controlled by a highly complex process. To better understand how energy homeostasis can be achieved, we describe a model that delineates the roles of individual hormonal and neuropeptide signalling pathways in the control of food intake and the means by which obesity can arise from inherited or acquired defects in their function.
6,178 citations
Book•
01 Jan 1999TL;DR: Communicating Systems: Behaviour of automata and Observation equivalence: theory, examples, and Discussion and related work Bibliography Index.
Abstract: Glossary Part I. Communicating Systems: 1. Introduction 2. Behaviour of automata 3. Sequential processes and bisimulation 4. Concurrent processes and reaction 5. Transitions and strong equivalence 6. Observation equivalence: theory 7. Observation equivalence: examples Part II. The pi-Calculus: 8. What is mobility? 9. The pi-calculus and reaction 10. Applications of the pi-calculus 11. Sorts, objects and functions 12. Commitments and strong bisimulation 13. Observation equivalence and examples 14. Discussion and related work Bibliography Index.
2,557 citations
"BioAmbients: an abstraction for bio..." refers background or methods in this paper
...[ 13 ] and references therein) do not provide such full guarded synchronous communication....
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...In our previous work [19], we developed an abstraction for biomolecular systems using the � -calculus process algebra [ 13 ], and extended the calculus to accurately handle the quantitative aspects of biochemical systems [17]....
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...Recent work [ 13 ] explores its adaptation to bio-graphs suitable for our biological variant of the ambient calculus....
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...Note that replication is taken as a primitive instead of recursion: this is commonly done in process calculi since replication is formally simpler to handle, and recursion can be easily derived from it [ 13 ]....
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