1,721,010 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A statistical and mechanistic, model-based analysis of spindle assembly checkpoint signalling
Full text linkThe mechanisms that ascertain whether a phase of the cell cycle has been successfully completed and the conditions to proceed to the next phase are fulfilled are called checkpoints. One of them is the spindle assembly checkpoint (SAC), which clears for completion of cell division only if the conditions for a proper partitioning of the genetic material are fulfilled. Despite complete knowledge of its function for decades, the underlying mechanism on themolecular level is still not completely elucidated.
We have data at hand that show how persistent the SAC is in individual yeast cells, when the amounts of its signalling components are altered. Since these manipulations are done on the genetic level, the effcacy is the same for each cell of a strain. Therefore, one would expect the SAC to show a homogeneous response in such a clonal population of cells. However, the data reveal that SAC persistence, measured as duration of cell cycle arrest in prometaphase, is highly variable between cells of the same strain.
In this thesis we use statistical modelling to quantify the observed cell-to-cell variability and analyse subpopulation structures in clonal populations of yeast cells. The sophisticated statistical analysis is complemented by mechanistic modelling of the molecular mechanism of the SAC on the population level.
The statistical analysis of the data is hampered by the fact that the data are censored, i.e. that prometaphase length as the variable of interest is not completely observable in many cells. To account for this in the analysis and to exploit the information which is only accessible by simultaneously analysing the data from multiple stains, we propose a general framework for multi-experiment mixture modelling, named MEMO. Employing this framework, we show that reduction of the amount of individual SAC proteins results in a split of the clonal population of cells into subpopulations with opposing SAC phenotypes. While one subpopulation retains a completely functional SAC, a second subpopulation with an impaired SAC emerges and increases. We quantify the sensitivity of this effect as a function of type and amount of the manipulated protein. Such a quantification allows for the prediction of the subpopulation structure of yet unobserved protein manipulations.
The striking observation of phenotypically different subpopulations in a population of genetically identical cells is underscored by the fact that noise in the protein abundances is small. We complement the statistical analysis of the data with mechanistic models of the molecular mechanism of SAC signalling. By exploiting the information contained in the population split, we identify ultrasensitivity and potential bistability to be a property of the dynamical system that forms the SAC. This implies high sensitivity with respect to noise in the abundance of signalling and targeted proteins. Furthermore, we assess the contribution of different SAC components to the observed cell-to-cell variability.
While the statistical modelling framework proposed in this thesis can help to prevent misinterpretation of data in the presence of censoring, also in other single-cell data settings, our findings on the properties of the SAC signalling system provide novel insights into this intricate molecular mechanism
Modeling SMS driven conversion of ceramide to sphingomyelin reveals the existence of a positive feedback mechanism
Full text linkIn questa tesi presentiamo un modello matematico minimo per la conversione di un ceramide in sfingomielina catalizzata dall'enzima sfingomielina sintasi 1 (SMS1) basato sulle leggi della cinetica chimica. Viene dimostrato, utilizzando tecniche di sampling per la stima parametrica e metodi di analisi matematica, che questo modello non è in grado di riprodurre qualitativamente delle misure sperimentali sulla composizioni dei lipidi in seguito ad alterazione dell'attivita enzimatica di SMS1. Concludiamo quindi che è necessario considerare un meccanismo di feedback positivo fra i prodotti e i reagenti della reazione, che esiste effettivamente in vivo tramite la proteina chinasi D e la proteina di trasporto di ceramide CERT.
Di conseguenza, proponiamo un secondo modello modificato in modo da comprendere questo meccanismo di feedback, che risulta essere in grado di spiegare i risultati sperimentali //
Here we present a minimal mathematical model for the Sphingomyelin synthase 1 (SMS1) driven conversion of ceramide to sphingomyelin based on chemical reaction kinetics. We demonstrate, via sampling-based parameter estimation and mathematical analysis, that this model is not able to qualitatively reproduce experimental measurements on lipid compositions after altering SMS1 activities. We conclude that a positive feedback mechanism is required from the products to the reactants of the reaction, which in fact exists in vivo via protein kinase D and the ceramide transfer protein CERT. Accordingly, a modified model that comprises this feedback mechanism was able to reproduce experimental findingsope
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Probabilistische Modellierung von Populationsvariabilität
No full textVincent Wagner's dissertation summarises progress in the probabilistic modelling of population variability. It comprises two chapters with complementary approaches to this challenging and broad topic. The first chapter deals with the Method of Moments for the Chemical Master Equation, while the second chapter uses random variable transformations to estimate distributed simulation model parameters
Understanding the mechanisms of robustness in intracellular protein signalling cascades and gene expression
Full text linkWe seek to understand the structural as well as the mechanistic basis of robustness in intracellular protein signalling cascades and in transcriptional regulation of gene expression. For protein signalling cascades, we employ a comparison based study involving a single, a double and a cascade of two double phosphorylation-dephosphorylation (PD) cycles. Using deterministic modelling approaches based on ordinary differential equations (ODE), we observe that the cascade of two double PD cycles exhibits robust output behaviour compared to that of a single and a double PD cycle upon constant as well as time- varying input perturbations. Furthermore, a system theoretic analysis reveals that the protein phosphorylation cascades act as an efficient low-pass filter that attenuates the noise mimicked as high-frequency input signals. Afterwards, we extend the study for a stochastic environment. Simulation results based on the stochastic simulation algorithm (SSA) reveal a novel phenomenon called dynamic sequestration that plays an ambivalent role as an intrinsic noise filter. Overall, the analysis indicates that complexity can be one of the basic principles of robust biological designs such as intracellular protein signalling cascades.
A major function of intracellular signalling cascades is to transmit the extracellular signal to the nucleus to initiate the process of gene expression. Gene expression is an intrinsically stochastic process that results into cell-to-cell variability in protein and messenger RNA (mRNA) levels, often termed as the expression noise. In spite of such noise, how cells achieve robustness is therefore a fundamental biological problem. We conclude the thesis by introducing a rule-based modelling approach based on the Kappa (κ) platform with the goal to understand the underlying mechanisms that ensure robust cellular functioning during gene expression. In particular, we introduce a gene expression model that keeps the process of transcription and excludes the process of translation. Therefore, we quantify the expression noise using mRNA which is the end product of transcription. Besides, the motivation behind adopting a rule-based modelling approach is that unlike the ODE-based approach, the former subsumes the combinatorial complexity arises due to various binding configurations of transcription factors (TF) for regulation of gene expression and offers a compact graphical representation of the same. Afterwards, the representation is transformed into an equivalent set of executable κ rules that are simulated using the SSA to obtain distributions of mRNA copy numbers corresponding to different regulatory mechanisms.Wir wollen sowohl die strukturellen als auch die mechanistischen Grundlagen der Robustheit in intrazellulären Proteinsignalkaskaden und in der transkriptionellen Regulation der Genexpression verstehen. Für die Untersuchung von Proteinsignalkaskaden verwenden wir eine vergleichsbasierte Studie mit einer Einzelphosphorylierung, einer Doppelphosphorylierung und einer Kaskade von zwei Doppelphosphorylierungs-Dephosphorylierungs-(PD)-Zyklen. Zur Modellierung verwenden wir deterministische Ansätze, die auf gewöhnlichen Differentialgleichungen (ODE) basieren. Im Gegensatz zu einem einzelnen und einem doppelten PD-Zyklus weist die Kaskade von zwei doppelten PD-Zyklen ein robustes Ausgabeverhalten bei konstanten sowie zeitvariablen Eingangsstörungen auf. Darüber hinaus zeigt eine systemtheoretische Analyse, dass die Proteinphosphorylierungskaskaden als effizienter Tiefpassfilter wirken, der hochfrequente Eingangssignale dämpft. Anschließend erweitern wir die Studie mit einer stochastischen Umgebung. Simulationsergebnisse, die auf dem stochastischen Simulationsalgorithmus (SSA) basieren, zeigen ein neuartiges Phänomen namens "Dynamic Sequestration", das eine ambivalente Rolle als intrinsischer Rauschfilter spielt. Insgesamt zeigt die Analyse, dass Komplexität eines der Grundprinzipien robuster biologischer Systeme wie intrazellulärer Proteinsignalkaskaden sein kann.
Eine der Hauptfunktionen intrazellulärer Signalkaskaden besteht darin das extrazelluläre Signal an den Kern zu übertragen, um den Prozess der Genexpression einzuleiten. Die Genexpression ist ein intrinsisch stochastischer Prozess, der zu einer Variabilität der Protein- und Messenger-RNA (mRNA)-Menge von Zelle zu Zelle führt, die oft als Expressionsrauschen bezeichnet wird. Trotz des Rauschens ist es daher ein grundlegendes biologisches Problem, wie Zellen ihre Robustheit erreichen. Um zugrunde liegende Mechanismen zu verstehen, die eine robuste zelluläre Funktion während der Genexpression gewährleisten, schließen wir die Arbeit mit der Einüfhrung eines regelbasierten Modellierungsansatzes auf Basis der Kappa (κ)-Plattform ab. Insbesondere stellen wir ein Genexpressionsmodell vor, das den Prozess der Transkription beibehält und den Prozess der Translation ausschließt. Daher quantifizieren wir das Expressionsrauschen mit Hilfe der mRNA, die das Endprodukt der Transkription ist. Darüber hinaus ist die Motivation für die Verwendung eines regelbasierten Modellierungsansatzes, dass im Gegensatz zum ODE-basierten Ansatz die kombinatorische Komplexität durch verschiedene Bindungskonfigurationen von Transkriptionsfaktoren (TF) zur Regulierung der Genexpression abgebildet wird und eine kompakte grafische Darstellung derselben geboten wird. Anschließend wird die Darstellung in einen äquivalenten Satz von ausführbaren κ-Regeln umgewandelt, die mit Hilfe der SSA simuliert werden, um Verteilungen von mRNA-Molekülen zu erhalten, die verschiedenen Regulationsmechanismen entsprechen.
Wir wollen sowohl die strukturellen als auch die mechanistischen Grundlagen der Robustheit in intrazellulären Proteinsignalkaskaden und in der transkriptionellen Regulation der Genexpression verstehen. Für die Untersuchung von Proteinsignalkaskaden verwenden wir eine vergleichsbasierte Studie mit einer Einzelphosphorylierung, einer Doppelphosphorylierung und einer Kaskade von zwei Doppelphosphorylierungs-Dephosphorylierungs-(PD)-Zyklen. Zur Modellierung verwenden wir deterministische Ansätze, die auf gewöhnlichen Differentialgleichungen (ODE) basieren. Im Gegensatz zu einem einzelnen und einem doppelten PD-Zyklus weist die Kaskade von zwei doppelten PD-Zyklen ein robustes Ausgabeverhalten bei konstanten sowie zeitvariablen Eingangsstörungen auf. Darüber hinaus zeigt eine systemtheoretische Analyse, dass die Proteinphosphorylierungskaskaden als effizienter Tiefpassfilter wirken, der hochfrequente Eingangssignale dämpft. Anschließend erweitern wir die Studie mit einer stochastischen Umgebung. Simulationsergebnisse, die auf dem stochastischen Simulationsalgorithmus (SSA) basieren, zeigen ein neuartiges Phänomen namens "Dynamic Sequestration", das eine ambivalente Rolle als intrinsischer Rauschfilter spielt. Insgesamt zeigt die Analyse, dass Komplexität eines der Grundprinzipien robuster biologischer Systeme wie intrazellulärer Proteinsignalkaskaden sein kann.
Eine der Hauptfunktionen intrazellulärer Signalkaskaden besteht darin das extrazelluläre Signal an den Kern zu übertragen, um den Prozess der Genexpression einzuleiten. Die Genexpression ist ein intrinsisch stochastischer Prozess, der zu einer Variabilität der Protein- und Messenger-RNA (mRNA)-Menge von Zelle zu Zelle führt, die oft als Expressionsrauschen bezeichnet wird. Trotz des Rauschens ist es daher ein grundlegendes biologisches Problem, wie Zellen ihre Robustheit erreichen. Um zugrunde liegende Mechanismen zu verstehen, die eine robuste zelluläre Funktion während der Genexpression gewährleisten, schließen wir die Arbeit mit der Einüfhrung eines regelbasierten Modellierungsansatzes auf Basis der Kappa (κ)-Plattform ab. Insbesondere stellen wir ein Genexpressionsmodell vor, das den Prozess der Transkription beibehält und den Prozess der Translation ausschließt. Daher quantifizieren wir das Expressionsrauschen mit Hilfe der mRNA, die das Endprodukt der Transkription ist. Darüber hinaus ist die Motivation für die Verwendung eines regelbasierten Modellierungsansatzes, dass im Gegensatz zum ODE-basierten Ansatz die kombinatorische Komplexität durch verschiedene Bindungskonfigurationen von Transkriptionsfaktoren (TF) zur Regulierung der Genexpression abgebildet wird und eine kompakte grafische Darstellung derselben geboten wird. Anschließend wird die Darstellung in einen äquivalenten Satz von ausführbaren κ-Regeln umgewandelt, die mit Hilfe der SSA simuliert werden, um Verteilungen von mRNA-Molekülen zu erhalten, die verschiedenen Regulationsmechanismen entsprechen
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