35 research outputs found
Two Decades of Maude
This paper is a tribute to José Meseguer, from the rest of us in the Maude team, reviewing the past, the present, and the future of the language and system with which we have been working for around two decades under his leadership. After reviewing the origins and the language's main features, we present the latest additions to the language and some features currently under development. This paper is not an introduction to Maude, and some familiarity with it and with rewriting logic are indeed assumed.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
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A review of modelling and verification approaches for computational biology
This paper reviews most frequently used computational modelling approaches and formal verification techniques in computational biology. The paper also compares a number of model checking tools and software suits used in analysing biological systems and biochemical networks and verifiying a wide range of biological properties
Probabilistic reasoning and inference for systems biology
One of the important challenges in Systems Biology is reasoning and performing hypotheses testing in uncertain conditions, when available knowledge may be incomplete and the experimental data may contain substantial noise.
In this thesis we develop methods of probabilistic reasoning and inference
that operate consistently within an environment of uncertain knowledge and data. Mechanistic mathematical models are used to describe hypotheses about biological systems.
We consider both deductive model based reasoning and model inference from data. The main contributions are a novel modelling approach using continuous time Markov chains that enables deductive derivation of model behaviours and their properties, and the application of Bayesian inferential methods to solve the inverse problem of model inference and comparison, given uncertain knowledge and noisy data.
In the first part of the thesis, we consider both individual and population
based techniques for modelling biochemical pathways using continuous time Markov chains, and demonstrate why the latter is the most appropriate. We illustrate a new approach, based on symbolic intervals of concentrations, with an example portion of the ERK signalling pathway. We demonstrate that the resulting model approximates the same dynamic system as traditionally defined using ordinary differential equations. The advantage of the new approach is quantitative logical analysis; we formulate a number of biologically significant queries in the temporal logic CSL and use probabilistic symbolic model checking to investigate their veracity.
In the second part of the thesis, we consider the inverse problem of model
inference and testing of alternative hypotheses, when models are defined by non-linear ordinary differential equations and the experimental data is noisy and sparse. We compare and evaluate a number of statistical techniques, and implement an effective Bayesian inferential framework for systems biology based on Markov chain Monte Carlo methods and estimation of marginal likelihoods by annealing-melting integration. We illustrate the framework with two case studies, one of which involves an open problem concerning the mediation of ERK phosphorylation in the ERK pathway
A Port Graph Calculus for Autonomic Computing and Invariant Verification
International audienceIn this paper, we first introduce port graphs as graphs with multiple edges and loops, with nodes having explicit connection points, called ports, and edges attaching to ports of nodes. We then define an abstract biochemical calculus that instantiates to a rewrite calculus on these graphs. Rules and strategies are themselves port graphs, i.e. first-class objects of the calculus. As a consequence, they can be rewritten as well, and rules can create new rules, providing a way of modeling adaptive systems. This approach also provides a formal framework to reason about computations and to verify useful properties. We show how structural properties of a modeled system can be expressed as strategies and checked for satisfiability at each step of the computation. This provides a way to ensure invariant properties of a system. This work is a contribution to the formal specification and verification of adaptive systems and to theoretical foundations ofautonomic computing
Compositional modelling of signalling pathways in timed concurrent constraint programming
International audienceThe biological data regarding the signalling pathways often consider single pathways or a small number of them. We propose a methodology for composing this kind of data in a coherent framework, in order to be able to investigate a bigger number of signalling pathways. We specify a biological system by means of a set of stoichiometric-like equations resembling the essential features of molecular interactions. We represent these equations by a timed concurrent constraint (ntcc) language, which can deal with partial information and the time for a reaction to occur. We describe a freely available prototypical implementation of our framework
Rule-based Methodologies for the Specification and Analysis of Complex Computing Systems
Desde los orígenes del hardware y el software hasta la época actual, la complejidad
de los sistemas de cálculo ha supuesto un problema al cual informáticos, ingenieros
y programadores han tenido que enfrentarse. Como resultado de este esfuerzo han
surgido y madurado importantes áreas de investigación. En esta disertación abordamos
algunas de las líneas de investigación actuales relacionada con el análisis y
la verificación de sistemas de computación complejos utilizando métodos formales y
lenguajes de dominio específico.
En esta tesis nos centramos en los sistemas distribuidos, con un especial interés por
los sistemas Web y los sistemas biológicos. La primera parte de la tesis está dedicada
a aspectos de seguridad y técnicas relacionadas, concretamente la certificación del
software. En primer lugar estudiamos sistemas de control de acceso a recursos y proponemos
un lenguaje para especificar políticas de control de acceso que están fuertemente
asociadas a bases de conocimiento y que proporcionan una descripción sensible
a la semántica de los recursos o elementos a los que se accede. También hemos desarrollado
un marco novedoso de trabajo para la Code-Carrying Theory, una metodología
para la certificación del software cuyo objetivo es asegurar el envío seguro de código
en un entorno distribuido. Nuestro marco de trabajo está basado en un sistema de
transformación de teorías de reescritura mediante operaciones de plegado/desplegado.
La segunda parte de esta tesis se concentra en el análisis y la verificación de sistemas
Web y sistemas biológicos. Proponemos un lenguaje para el filtrado de información
que permite la recuperación de informaciones en grandes almacenes de datos. Dicho
lenguaje utiliza información semántica obtenida a partir de ontologías remotas
para re nar el proceso de filtrado. También estudiamos métodos de validación para
comprobar la consistencia de contenidos web con respecto a propiedades sintácticas
y semánticas. Otra de nuestras contribuciones es la propuesta de un lenguaje que
permite definir y comprobar automáticamente restricciones semánticas y sintácticas
en el contenido estático de un sistema Web. Finalmente, también consideramos los
sistemas biológicos y nos centramos en un formalismo basado en lógica de reescritura
para el modelado y el análisis de aspectos cuantitativos de los procesos biológicos.
Para evaluar la efectividad de todas las metodologías propuestas, hemos prestado
especial atención al desarrollo de prototipos que se han implementado utilizando
lenguajes basados en reglas.Baggi ., M. (2010). Rule-based Methodologies for the Specification and Analysis of Complex Computing Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8964Palanci
Modelling and analysis of structure in cellular signalling systems
Cellular signalling is an important area of study in biology. Signalling pathways are well-known abstractions that explain the mechanisms whereby cells respond to signals. Collections of pathways form signalling networks, and interactions between pathways in a network, known as cross-talk, enables further complex signalling behaviours. Increasingly, computational modelling and analysis is required to handle the complexity of such systems.
While there are several computational modelling approaches for signalling pathways, none make cross-talk explicit. We present a modular modelling framework for pathways and their cross-talk. Networks are formed by composing pathways: different cross-talks result from different synchronisations of reactions between, and overlaps of, the pathways. We formalise five types of cross-talk and give approaches to reason about possible cross-talks in a network.
The complementary problem is how to handle unstructured signalling networks, i.e. networks with no explicit notion of pathways or cross-talk. We present an approach to better understand unstructured signalling networks by modelling them as a set of signal flows through the network. We introduce the Reaction Minimal Paths (RMP) algorithm that computes the set of signal flows in a model. To the best of our knowledge, current algorithms cannot guarantee both correctness and completeness of the set of signal flows in a model. The RMP algorithm is the first.
Finally, the RMP algorithm suffers from the well-known state space explosion problem. We use suitable partial order reduction algorithms to improve the efficiency of this algorithm
Pathway Semantics: An Algebraic Data Driven Algorithm to Generate Hypotheses about Molecular Patterns Underlying Disease Progression
The overarching goal of the Pathway Semantics Algorithm (PSA) is to improve the in silico identification of clinically useful hypotheses about molecular patterns in disease progression. By framing biomedical questions within a variety of matrix representations, PSA has the flexibility to analyze combined quantitative and qualitative data over a wide range of stratifications. The resulting hypothetical answers can then move to in vitro and in vivo verification, research assay optimization, clinical validation, and commercialization. Herein PSA is shown to generate novel hypotheses about the significant biological pathways in two disease domains: shock / trauma and hemophilia A, and validated experimentally in the latter. The PSA matrix algebra approach identified differential molecular patterns in biological networks over time and outcome that would not be easily found through direct assays, literature or database searches.
In this dissertation, Chapter 1 provides a broad overview of the background and motivation for the study, followed by Chapter 2 with a literature review of relevant computational methods. Chapters 3 and 4 describe PSA for node and edge analysis respectively, and apply the method to disease progression in shock / trauma. Chapter 5 demonstrates the application of PSA to hemophilia A and the validation with experimental results. The work is summarized in Chapter 6, followed by extensive references and an Appendix with additional material
Notas sobre Soft Sets - Preliminaries
[ES]Muchos problemas de la vida real requieren el uso de datos imprecisos o inciertos. Su análisis debe implicar la aplicación de principios matemáticos capaces de captar estas características. La teoría de los conjuntos difusos supuso un cambio paradigmático en las Matemáticas al permitir la pertenencia parcial. Para una definición y argumentos acerca de su aplicabilidad a varios campos, nos interesa especialmente una generalización de los conjuntos difusos: la aplicación de la teoría de los soft sets y sus extensiones a los problemas de toma de decisiones
Rule-based Modeling of Cell Signaling: Advances in Model Construction, Visualization and Simulation
Rule-based modeling is a graph-based approach to specifying the kinetics of cell signaling
systems. A reaction rule is a compact and explicit graph-based representation of a kinetic process,
and it matches a class of reactions that involve identical sites and identical kinetics. Compact rule-
based models have been used to generate large and combinatorially complex reaction networks,
and rules have also been used to compile databases of kinetic interactions targeting specific cells
and pathways. In this work, I address three technological challenges associated with rule-based
modeling. First, I address the ability to generate an automated global visualization of a rule-based
model as a network of signal flows. I showed how to analyze a reaction rule and extract a set of
bipartite regulatory relationships, which can be aggregated across rules into a global network. I
also provide a set of coarse-graining approaches to compress an automatically generated network
into a compact pathway diagram, even for models with 100s of rules. Second, I resolved an
incompatibility between two recent advances in rule-based modeling: network-free simulation
(which enables simulation without generating a reaction network), and energy-based rule-based
modeling (which enables specifying a model using cooperativity parameters and automated
accounting of free energy). The incompatibility arose because calculating the reaction rate requires
computing the reaction free energy in an energy-based model, and this requires knowledge of both
reactants and products of the reaction, but the products are not available in a network-free
simulation until after the reaction event has fired. This was resolved by expanding each energy-
based rule into a number of normal reaction rules for which reaction free energies can be calculated
unambiguously. Third, I demonstrated a particular type of modularization that is based on treating
a set of rules as a module. This enables building models from combinations of modular hypotheses
and supplements the other modularization strategies such as macros, types and energy-based
compression