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A Monte Carlo model checker for probabilistic LTL with numerical constraints
We define the syntax and semantics of a new temporal logic called probabilistic LTL with numerical constraints (PLTLc).
We introduce an efficient model checker for PLTLc properties. The efficiency of the model checker is through approximation
using Monte Carlo sampling of finite paths through the model’s state space (simulation outputs) and parallel model checking
of the paths. Our model checking method can be applied to any model producing quantitative output – continuous or
stochastic, including those with complex dynamics and those with an infinite state space. Furthermore, our offline approach
allows the analysis of observed (real-life) behaviour traces. We find in this paper that PLTLc properties with constraints
over free variables can replace full model checking experiments, resulting in a significant gain in efficiency. This overcomes
one disadvantage of model checking experiments which is that the complexity depends on system granularity and number of
variables, and quickly becomes infeasible. We focus on models of biochemical networks, and specifically in this paper on
intracellular signalling pathways; however our method can be applied to a wide range of biological as well as technical
systems and their models. Our work contributes to the emerging field of synthetic biology by proposing a rigourous approach
for the structured formal engineering of biological systems
Petri nets for systems and synthetic biology
We give a description of a Petri net-based framework for
modelling and analysing biochemical pathways, which uni¯es the qualita-
tive, stochastic and continuous paradigms. Each perspective adds its con-
tribution to the understanding of the system, thus the three approaches
do not compete, but complement each other. We illustrate our approach
by applying it to an extended model of the three stage cascade, which
forms the core of the ERK signal transduction pathway. Consequently
our focus is on transient behaviour analysis. We demonstrate how quali-
tative descriptions are abstractions over stochastic or continuous descrip-
tions, and show that the stochastic and continuous models approximate
each other. Although our framework is based on Petri nets, it can be
applied more widely to other formalisms which are used to model and
analyse biochemical networks
Controlled vocabularies and semantics in systems biology
The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments
Complementary approaches to understanding the plant circadian clock
Circadian clocks are oscillatory genetic networks that help organisms adapt
to the 24-hour day/night cycle. The clock of the green alga Ostreococcus tauri
is the simplest plant clock discovered so far. Its many advantages as an
experimental system facilitate the testing of computational predictions.
We present a model of the Ostreococcus clock in the stochastic process
algebra Bio-PEPA and exploit its mapping to different analysis techniques, such
as ordinary differential equations, stochastic simulation algorithms and
model-checking. The small number of molecules reported for this system tests
the limits of the continuous approximation underlying differential equations.
We investigate the difference between continuous-deterministic and
discrete-stochastic approaches. Stochastic simulation and model-checking allow
us to formulate new hypotheses on the system behaviour, such as the presence of
self-sustained oscillations in single cells under constant light conditions.
We investigate how to model the timing of dawn and dusk in the context of
model-checking, which we use to compute how the probability distributions of
key biochemical species change over time. These show that the relative
variation in expression level is smallest at the time of peak expression,
making peak time an optimal experimental phase marker. Building on these
analyses, we use approaches from evolutionary systems biology to investigate
how changes in the rate of mRNA degradation impacts the phase of a key protein
likely to affect fitness. We explore how robust this circadian clock is towards
such potential mutational changes in its underlying biochemistry. Our work
shows that multiple approaches lead to a more complete understanding of the
clock
05441 Abstracts Collection -- Managing and Mining Genome Information: Frontiers in Bioinformatics
From 30.10.05 to 04.11.05, the Dagstuhl Seminar 05441 ``Managing and Mining Genome Information: Frontiers in Bioinformatics\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available
Model building and model checking for biochemical processes
A central claim of computational systems biology is that, by drawing on mathematical approaches developed in the context of dynamic systems, kinetic analysis, computational theory and logic, it is possible to create powerful simulation, analysis, and reasoning tools for working biologists to decipher existing data, devise new experiments, and ultimately to understand functional properties of genomes, proteomes, cells, organs, and organisms. In this article, a novel computational tool is described that achieves many of the goals of this new discipline. The novelty of this system involves an automaton-based semantics of the temporal evolution of complex biochemical reactions starting from the representation given as a set of differential equations. The related tools also provide ability to qualitatively reason about the systems using a propositional temporal logic that can express an ordered sequence of events succinctly and unambiguously. The implementation of mathematical and computational models in the Simpathica and XSSYS systems is described briefly. Several example applications of these systems to cellular and biochemical processes are presented: the two most prominent are Leibler et al.'s repressilator (an artificial synthesized oscillatory network), and Curto-Voit-Sorribas-Cascante's purine metabolism reaction model
A service-oriented architecture for integrating the modeling and formal verification of genetic regulatory networks
<p>Abstract</p> <p>Background</p> <p>The study of biological networks has led to the development of increasingly large and detailed models. Computer tools are essential for the simulation of the dynamical behavior of the networks from the model. However, as the size of the models grows, it becomes infeasible to manually verify the predictions against experimental data or identify interesting features in a large number of simulation traces. Formal verification based on temporal logic and model checking provides promising methods to automate and scale the analysis of the models. However, a framework that tightly integrates modeling and simulation tools with model checkers is currently missing, on both the conceptual and the implementational level.</p> <p>Results</p> <p>We have developed a generic and modular web service, based on a service-oriented architecture, for integrating the modeling and formal verification of genetic regulatory networks. The architecture has been implemented in the context of the qualitative modeling and simulation tool G<smcaps>NA</smcaps> and the model checkers N<smcaps>U</smcaps>SMV and C<smcaps>ADP</smcaps>. G<smcaps>NA</smcaps> has been extended with a verification module for the specification and checking of biological properties. The verification module also allows the display and visual inspection of the verification results.</p> <p>Conclusions</p> <p>The practical use of the proposed web service is illustrated by means of a scenario involving the analysis of a qualitative model of the carbon starvation response in <it>E. coli</it>. The service-oriented architecture allows modelers to define the model and proceed with the specification and formal verification of the biological properties by means of a unified graphical user interface. This guarantees a transparent access to formal verification technology for modelers of genetic regulatory networks.</p
A framework for modelling Molecular Interaction Maps
Metabolic networks, formed by a series of metabolic pathways, are made of
intracellular and extracellular reactions that determine the biochemical
properties of a cell, and by a set of interactions that guide and regulate the
activity of these reactions. Most of these pathways are formed by an intricate
and complex network of chain reactions, and can be represented in a human
readable form using graphs which describe the cell cycle checkpoint pathways.
This paper proposes a method to represent Molecular Interaction Maps
(graphical representations of complex metabolic networks) in Linear Temporal
Logic. The logical representation of such networks allows one to reason about
them, in order to check, for instance, whether a graph satisfies a given
property , as well as to find out which initial conditons would guarantee
, or else how can the the graph be updated in order to satisfy .
Both the translation and resolution methods have been implemented in a tool
capable of addressing such questions thanks to a reduction to propositional
logic which allows exploiting classical SAT solvers.Comment: 31 pages, 12 figure
An introduction to Graph Data Management
A graph database is a database where the data structures for the schema
and/or instances are modeled as a (labeled)(directed) graph or generalizations
of it, and where querying is expressed by graph-oriented operations and type
constructors. In this article we present the basic notions of graph databases,
give an historical overview of its main development, and study the main current
systems that implement them
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