95 research outputs found

    Words fixing the kernel network and maximum independent sets in graphs

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    The simple greedy algorithm to find a maximal independent set of a graph can be viewed as a sequential update of a Boolean network, where the update function at each vertex is the conjunction of all the negated variables in its neighbourhood. In general, the convergence of the so-called kernel network is complex. A word (sequence of vertices) fixes the kernel network if applying the updates sequentially according to that word. We prove that determining whether a word fixes the kernel network is coNP-complete. We also consider the so-called permis, which are permutation words that fix the kernel network. We exhibit large classes of graphs that have a permis, but we also construct many graphs without a permis

    Combining Boolean Networks and Ordinary Differential Equations for Analysis and Comparison of Gene Regulatory Networks

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    This thesis is concerned with different groups of qualitative models of gene regulatory networks. Four types of models will be considered: interaction graphs, Boolean networks, models based on differential equations and discrete abstractions of differential equations. We will investigate the relations between these modeling frameworks and how they can be used in the analysis of individual models. The focus lies on the mathematical analysis of these models. This thesis makes several contributions in relating these different modeling frameworks. The first approach concerns individual Boolean models and parametrized families of ordinary differential equations (ODEs). To construct ODE models systematically from Boolean models several automatic conversion algorithms have been proposed. In Chapter 2 several such closely related algorithms will be considered. It will be proven that certain invariant sets are preserved during the conversion from a Boolean network to a model based on ODEs. In the second approach the idea of abstracting the dynamics of individual models to relate structure and dynamics will be introduced. This approach will be applied to Boolean models and models based on differential equations. This allows to compare groups of models in these modeling frameworks which have the same structure. We demonstrate that this constitutes an approach to link the interaction graph to the dynamics of certain sets of Boolean networks and models based on differential equations. The abstracted dynamics – or more precisely the restrictions on the abstracted behavior – of such sets of Boolean networks or models based on differential equations will be represented as Boolean state transitions graphs themselves. We will show that these state transition graphs can be considered as asynchronous Boolean networks. Despite the rather theoretical question this thesis tries to answer there are many potential applications of the results. The results in Chapter 2 can be applied to network reduction of ODE models based on Hill kinetics. The results of the second approach in Chapter 4 can be applied to network inference and analysis of Boolean model sets. Furthermore, in the last chapter of this thesis several ideas for applications with respect to experiment design will be considered. This leads to the question how different asynchronous Boolean networks or different behaviours of a single asynchronous Boolean network can be distinguishedDiese Arbeit beschäftigt sich mit unterschiedlichen Typen von qualitativen Modellen genregulatorischer Netzwerke. Vier Typen von Modellen werden betrachtet: Interaktionsgraphen, Boolesche Netzwerke, Modelle, die auf Differentialgleichungen basieren und diskrete Abstraktionen von Differentialgleichungen. Wir werden mehr über die Beziehungen zwischen diesen Modellgruppen lernen und wie diese Beziehungen genutzt werden können, um einzelne Modelle zu analysieren. Der Schwerpunkt liegt hierbei auf der mathematischen Analyse dieser Modellgruppen. In dieser Hinsicht leistet diese Arbeit mehrere Beiträge. Zunächst betrachten wir Boolesche Netzwerke und parametrisierte Familien von gewöhnlichen Differentialgleichungen (ODEs). Um solche ODE-Modelle systematisch aus Booleschen Modellen abzuleiten, wurden in der Vergangenheit verschiedene automatische Konvertierungsalgorithmen vorgeschlagen. In Kapitel 2 werden einige dieser Algorithmen näher untersucht. Wir werden beweisen, dass bestimmte invariante Mengen bei der Konvertierung eines Booleschen Modells in ein ODE-Modell erhalten bleiben. Der zweite Ansatz, der in dieser Arbeit verfolgt wird, beschäftigt sich mit diskreten Abstraktionen der Dynamik von Modellen. Mit Hilfe dieser Abstraktionen ist es möglich, die Struktur – den Interaktionsgraphen – und die Dynamik der zugehörigen Modelle in Bezug zu setzen. Diese Methode wird sowohl auf Boolesche Modelle als auch auf ODE-Modelle angewandt. Gleichzeitig erlaubt dieser Ansatz Mengen von Modellen in unterschiedlichen Modellgruppen zu vergleichen, die dieselbe Struktur haben. Die abstrahierten Dynamiken (genauer die Einschränkungen der abstrahierten Dynamiken) der Booleschen Modellmengen oder ODE-Modellmengen können als Boolesche Zustandsübergangsgraphen repräsentiert werden. Wir werden zeigen, dass diese Zustandsübergangsgraphen wiederum selber als (asynchrone) Boolesche Netzwerke aufgefasst werden können. Trotz der theoretischen Ausgangsfrage werden in dieser Arbeit zahlreiche Anwendungen aufgezeigt. Die Ergebnisse aus Kapitel 2 können zur Modellreduktion benutzt werden, indem die Dynamik der ODE-Modelle auf den zu den Booleschen Netzwerken gehörigen “trap spaces” betrachtet wird. Die Resultate aus Kapitel 4 können zur Netzwerkinferenz oder zur Analyse von Modellmengen genutzt werden. Weiterhin werden im letzten Kapitel dieser Arbeit einige Anwendungsideen im Bezug auf Experimentdesign eingeführt. Dies führt zu der Fragestellung, wie verschiedene asynchrone Boolesche Netzwerke oder unterschiedliche Dynamiken, die mit einem einzelnen Modell vereinbar sind, unterschieden werden können

    Prevalence and recoverability of syntactic parameters in sparse distributed memories

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    We propose a new method, based on sparse distributed memory, for studying dependence relations between syntactic parameters in the Principles and Parameters model of Syntax. By storing data of syntactic structures of world languages in a Kanerva network and checking recoverability of corrupted data from the network, we identify two different effects: an overall underlying relation between the prevalence of parameters across languages and their degree of recoverability, and a finer effect that makes some parameters more easily recoverable beyond what their prevalence would indicate. The latter can be seen as an indication of the existence of dependence relations, through which a given parameter can be determined using the remaining uncorrupted data

    Compiling higher-order specifications to SMT solvers : how to deal with rejection constructively

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    Modern verification tools frequently rely on compiling high-level specifications to SMT queries. However, the high-level specification language is usually more expressive than the available solvers and therefore some syntactically valid specifications must be rejected by the tool. In such cases, the challenge is to provide a comprehensible error message to the user that relates the original syntactic form of the specification to the semantic reason it has been rejected. In this paper we demonstrate how this analysis may be performed by combining a standard unification-based type-checker with type classes and automatic generalisation. Concretely, type-checking is used as a constructive procedure for under-approximating whether a given specification lies in the subset of problems supported by the solver. Any resulting proof of rejection can be transformed into a detailed explanation to the user. The approach is compositional and does not require the user to add extra typing annotations to their program. We subsequently describe how the type system may be leveraged to provide a sound and complete compilation procedure from suitably typed expressions to SMT queries, which we have verified in Agda

    Warranty prediction during product development: Developing an event generation engine in an engineer-to-order environment

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    In order for manufacturing companies to stay competitive, it is necessary to drive warranty system improvements in terms of improved product reliability, improved service delivery efficiency and properly designed warranty policies. However, traditional methods for assessing warranty performance are not always sufficient to alert product development teams of the impending warranty issues. Furthermore, improved assessment methods are needed to aid product development teams make decisions related to the warranty performance of the product. The focus of this research was to develop a framework to integrate statistical inference methods and data mining techniques to create a warranty event generation framework. This was done on the context of an engineer-to-order product development environment. The objectives of this work were: (1) to develop an inference model for the integration of disparate data sources; (2) to demonstrate that multiple data streams can be conditioned for input into the above inference model; (3) to develop the above model and process in light of actual data. This thesis will report on the progress and challenges that have been made toward fulfilling these objectives. The thesis closes by outlining the future research agenda for developing a warranty event generation engine that can integrate data from disparate data sources

    Approximation Algorithms for Broadcasting in Flower Graphs

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    Over the last century, telecommunication networks have become the nervous system of our society. As data is generated and stored on varied nodes, effective communication is imperative to ensure efficient use of the network. Our ever-growing reliance on these increasingly large and complex networks make ineffective communication strategies evermore apparent. Broadcasting is a fundamental information-dissemination problem which models communication across a connected graph in the following manner: a single vertex, the originator, seeks to pass some message along to all other vertices in the graph. In general, research on broadcasting can be grouped in roughly two categories: Firstly, given some particular graph and some particular vertex chosen to be originator, what is a broadcast scheme that informs the entire graph in the minimum time possible? Secondly, given some number of nodes, how can we arrange them in a particular network topology such that we can achieve minimal broadcast time from any vertex? This thesis focuses on problems of the first category. Finding the minimum broadcast time of any vertex in an arbitrary graph is NP-Complete, but efficient algorithms have been found for particular graph families. In particular, polynomial time algorithms have been found for trees and some tree-like graphs: unicyclic graphs, tree of cycles. Such algorithms have also been found for some graphs with no intersecting cliques, such as fully connected trees and trees of cliques. Finally, graphs containing cycles with particular restrictions were also studied, and efficient algorithms for necklace graphs and k-restricted cactus graphs were also found. The question still stands however, of whether these restrictions may be too conservative, and that efficient algorithms exist on broader classes of graphs. In particular, significant research has been made towards finding an efficient broadcasting algorithm on cactus graphs, which has not been found so far. This thesis studies the broadcasting problem on Flower graphs, which capture the difficulty of cactus graphs in a simple graph family. Flower graphs, or k-cycle graphs, are graphs composed of k cycles all joined on a single central vertex v_c. The contributions of this thesis for broadcasting on flower graphs is two-fold: it first improves the approximation ratio for broadcasting on flower graphs. It then provides a heuristic which performs significantly better in practice than the current best heuristic. We also demonstrate that our heuristic finds the optimal broadcast time for particular subcases of flower graphs

    Optimisation of stem cell based approaches towards cardiac regeneration

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    Aberrant behaviour of resident cells causes several illnesses. Among them, cardiovascular diseases are the leading cause of death in the western world. The human heart possesses only negligible myocardial regeneration capacity after a myocardial infarction, thus, it cannot compensate the massive cell loss self-reliantly. The thesis addresses the optimization of different cell biological approaches for enrichment of cardiac subtypes. Moreover, the thesis demonstrates different genetic manipulation strategies (DNA-, mRNA- and microRNA-based) for an efficient modulation of cell fate.Abnormales Verhalten von körpereigenen Zellen führt zu zahlreichen Krankheitsbildern, unter diesen stellen kardiovaskuläre Krankheiten die Haupttodesursache in der westlichen Welt dar. Das menschliche Herz weist jedoch nur ein geringes Regenerationspotenzial nach einem Myokardinfarkt auf, wodurch der massive Zellverlust nicht selbstständig kompensiert werden kann. Diese Dissertation befasst sich mit der Optimierung verschiedener zellbiologischer Ansätze zur Anreicherung kardialer Subtypen sowie verschiedener Strategien der genetischen Manipulation zur Modulation des Zellschicksals

    Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

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    The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer-reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state-of-the-art handbook for basic and clinical researchers
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