767 research outputs found
Process Calculi Abstractions for Biology
Several approaches have been proposed to model biological systems by means of the formal techniques and tools available in computer science. To mention just a few of them, some representations are inspired by Petri Nets theory, and some other by stochastic processes. A most recent approach consists in interpreting the living entities as terms of process calculi where the behavior of the represented systems can be inferred by applying syntax-driven rules. A comprehensive picture of the state of the art of the process calculi approach to biological modeling is still missing. This paper goes in the direction of providing such a picture by presenting a comparative survey of the process calculi that have been used and proposed to describe the behavior of living entities. This is the preliminary version of a paper that was published in Algorithmic Bioprocesses. The original publication is available at http://www.springer.com/computer/foundations/book/978-3-540-88868-
Verification of Spatial and Temporal Modalities in Biochemical Systems
AbstractBiochemical systems such as metabolic and signaling pathways tend to be arranged in a physical space: the product of one reaction must be in the right place to become the reactant for the subsequent reaction in the pathway. Moreover, in some cases, the behavior of the systems can depend on both, the location of the reactants as well as on the time needed for the reaction to occur. We address the problem of specifying and verifying properties of biochemical systems that exhibit both temporal and spatial modalities at the same time. For that, we use as specification language a fragment of intuitionistic linear logic with subexponentials (SELL). The subexponential signature allows us to capture the spatial relations among the different components of the system and the timed constraints for reactions to occur. We show that our framework is general enough to give a declarative semantics to P-Systems and we show that such logical characterization has a strong level of adequacy. Hence, derivations in SELL follow exactly the behavior of the modeled system
Types for BioAmbients
The BioAmbients calculus is a process algebra suitable for representing
compartmentalization, molecular localization and movements between
compartments. In this paper we enrich this calculus with a static type system
classifying each ambient with group types specifying the kind of compartments
in which the ambient can stay. The type system ensures that, in a well-typed
process, ambients cannot be nested in a way that violates the type hierarchy.
Exploiting the information given by the group types, we also extend the
operational semantics of BioAmbients with rules signalling errors that may
derive from undesired ambients' moves (i.e. merging incompatible tissues).
Thus, the signal of errors can help the modeller to detect and locate unwanted
situations that may arise in a biological system, and give practical hints on
how to avoid the undesired behaviour
Multi-Level Kinetic Model of mRNA Delivery via Transfection of Lipoplexes
Recent work on the use of mRNA lipoplexes for gene delivery demonstrates the need for a mathematical model that simulates and predicts kinetics and transfection efficiency. The small copy numbers involved make it necessary to use stochastic models and include statistical analysis of the variation observed in the experimental data. The modeling requirements are further complicated by the multi-level nature of the problem, where mRNA molecules are contained in lipoplexes, which are in turn contained in endosomes, where each of these entities displays a behavior of its own. We have created a mathematical model that reproduces both the time courses and the statistical variance observed in recent experiments using single-cell tracking of GFP expression after transfection. By applying a few key simplifications and assumptions, we have limited the number of free parameters to five, which we optimize to match five experimental determinants by means of a simulated annealing algorithm. The models demonstrate the need for modeling of nested species in order to reproduce the shape of the dose-response and expression-level curves
Multi-Level Kinetic Model of mRNA Delivery via Transfection of Lipoplexes
Recent work on the use of mRNA lipoplexes for gene delivery demonstrates the need for a mathematical model that simulates and predicts kinetics and transfection efficiency. The small copy numbers involved make it necessary to use stochastic models and include statistical analysis of the variation observed in the experimental data. The modeling requirements are further complicated by the multi-level nature of the problem, where mRNA molecules are contained in lipoplexes, which are in turn contained in endosomes, where each of these entities displays a behavior of its own. We have created a mathematical model that reproduces both the time courses and the statistical variance observed in recent experiments using single-cell tracking of GFP expression after transfection. By applying a few key simplifications and assumptions, we have limited the number of free parameters to five, which we optimize to match five experimental determinants by means of a simulated annealing algorithm. The models demonstrate the need for modeling of nested species in order to reproduce the shape of the dose-response and expression-level curves
A Process Calculus for Molecular Interaction Maps
We present the MIM calculus, a modeling formalism with a strong biological
basis, which provides biologically-meaningful operators for representing the
interaction capabilities of molecular species. The operators of the calculus
are inspired by the reaction symbols used in Molecular Interaction Maps (MIMs),
a diagrammatic notation used by biologists. Models of the calculus can be
easily derived from MIM diagrams, for which an unambiguous and executable
interpretation is thus obtained. We give a formal definition of the syntax and
semantics of the MIM calculus, and we study properties of the formalism. A case
study is also presented to show the use of the calculus for modeling
biomolecular networks.Comment: 15 pages; 8 figures; To be published on EPTCS, proceedings of MeCBIC
200
A Taxonomy of Causality-Based Biological Properties
We formally characterize a set of causality-based properties of metabolic
networks. This set of properties aims at making precise several notions on the
production of metabolites, which are familiar in the biologists' terminology.
From a theoretical point of view, biochemical reactions are abstractly
represented as causal implications and the produced metabolites as causal
consequences of the implication representing the corresponding reaction. The
fact that a reactant is produced is represented by means of the chain of
reactions that have made it exist. Such representation abstracts away from
quantities, stoichiometric and thermodynamic parameters and constitutes the
basis for the characterization of our properties. Moreover, we propose an
effective method for verifying our properties based on an abstract model of
system dynamics. This consists of a new abstract semantics for the system seen
as a concurrent network and expressed using the Chemical Ground Form calculus.
We illustrate an application of this framework to a portion of a real
metabolic pathway
A Global Occurrence Counting Analysis for Brane Calculi
We propose a polynomial static analysis for Brane Calculi, based on Abstract Interpretation techniques. The analysis provides a description of the possible hierarchical structure of membranes and of the processes possibly associated to each membrane, together with global occurrence counting information. Our analysis
can be applied in the biological setting to investigate systems in which the information
on the number of membranes occurring in the system plays a crucial role
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