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Dissertations / Theses on the topic 'G-Computation'

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Published: 25 January 2025

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1

Sirota, Leite Fernanda. "Role of the amino acid sequences in domain swapping of the B1 domain of protein G by computation analysis." Doctoral thesis, Universite Libre de Bruxelles, 2007. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210657.

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Domain swapping is a wide spread phenomenon which involves the association between two or more protein subunits such that intra-molecular interactions between domains in each subunit are replaced by equivalent inter-molecular interactions between the same domains in different subunits. This thesis is devoted to the analysis of the factors that drive proteins to undergo such association modes. The specific system analyzed is the monomer to swapped dimer formation of the B1 domain of the immunoglobulin G binding protein (GB1). The formation of this dimer was shown to be fostered by 4 amino acid substitutions (L5V, F30V, Y33F, A34F) (Byeon et al. 2003). In this work, computational protein design and molecular dynamics simulations, both with detailed atomic models, were used to gain insight into how these 4 mutations may promote the domain swapping reaction.

The stability of the wt and quadruple mutant GB1 monomers was assessed using the software DESIGNER, a fully automatic procedure that selects amino acid sequences likely to stabilize a given backbone structure (Wernisch et al. 2000). Results suggest that 3 of the mutations (L5V, F30V, A34F) have a destabilizing effect. The first mutation (L5V) forms destabilizing interactions with surrounding residues, while the second (F30V) is engaged in unfavorable interactions with the protein backbone, consequently causing local strain. Although the A34F substitution itself is found to contribute favorably to the stability of the monomer, this is achieved only at the expense of forcing the wild type W43 into a highly strained conformation concomitant with the formation of unfavorable interactions with both W43 and V54.

Finally, we also provide evidence that A34F mutation stabilizes the swapped dimer structure. Although we were unable to perform detailed protein design calculations on the dimer, due to the lower accuracy of the model, inspection of its 3D structure reveals that the 34F side chains pack against one another in the core of the swapped structure, thereby forming extensive non-native interactions that have no counterparts in the individual monomers. Their replacement by the much smaller Ala residue is suggested to be significantly destabilizing by creating a large internal cavity, a phenomenon, well known to be destabilizing in other proteins. Our analysis hence proposes that the A34F mutation plays a dual role, that of destabilizing the GB1 monomer structure while stabilizing the swapped dimer conformation.

In addition to the above study, molecular dynamics simulations of the wild type and modeled quadruple mutant GB1 structures were carried out at room and elevated temperatures (450 K) in order to sample the conformational landscape of the protein near its native monomeric state, and to characterize the deformations that occur during early unfolding. This part of the study was aimed at investigating the influence of the amino acid sequence on the conformational properties of the GB1 monomer and the possible link between these properties and the swapping process. Analysis of the room temperature simulations indicates that the mutant GB1 monomer fluctuates more than its wild type counter part. In addition, we find that the C-terminal beta-hairpin is pushed away from the remainder of the structure, in agreement with the fact that this hairpin is the structural element that is exchanged upon domain swapping. The simulations at 450 K reveal that the mutant protein unfolds more readily than the wt, in agreement with its decreased stability. Also, among the regions that unfold early is the alpha-helix C-terminus, where 2 out of the 4 mutations reside. NMR experiments by our collaborators have shown this region to display increased flexibility in the monomeric state of the quadruple mutant.

Our atomic scale investigation has thus provided insights into how sequence modifications can foster domain swapping of GB1. Our findings indicate that the role of the amino acid substitutions is to decrease the stability of individual monomers while at the same time increase the stability of the swapped dimer, through the formation of non-native interactions. Both roles cooperate to foster swapping.
Doctorat en sciences, Spécialisation biologie moléculaire
info:eu-repo/semantics/nonPublished

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2

Breuer, Thomas [Verfasser], Regina [Akademischer Betreuer] Dittmann, and Tobias G. [Akademischer Betreuer] Noll. "Development of ReRAM-based devices for logic- and computation-in-memory applications / Thomas Breuer ; Regina Dittmann, Tobias G. Noll." Aachen : Universitätsbibliothek der RWTH Aachen, 2017. http://d-nb.info/1162499680/34.

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3

Higgs, C. "A computational study of the G-protein-G-protein coupled receptor interaction." Thesis, University of Essex, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324216.

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4

Taddese, Bruck. "Computational modelling of G protein-coupled receptors." Thesis, University of Essex, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.589439.

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G protein-coupled receptors (GPCRs) comprise the most "drugable" family of transmembrane proteins, GPCRs share a common structural template and a general mechanism of signal transduction, but vary greatly in sequence conservation, ligand recognition and function. The current set of class A GPCR crystal structures have facilitated the modelling of class A GPCRs. However, other classes of GPCRs have not been so easy to study. The main focus presented in this thesis is the utilisation of class A GPCR structural information to model medically important GPCRs other than class A GPCRs via molecular modelling. The lack of sequence conservation hampers modelling non-class A GPCRs using class A GPCR crystal structures. A plant GPCR, namely GCR1, has sequence homology to more than one GPCR family (class A, Band E GPCRs) and has been used to align the transmembrane region of class A and B GPCRs. Consequently, we have presented a computational protocol for the identification of putative plant GPCRs that may similarly be used to address the difficult issue of alignment between GPCR families but in this respect only GCR1 was found to be useful. GCR1 is still an orphan GPCR with no known cognate ligand. We first assessed whether GCR 1 was a valid GPCR via homology modelling and molecular dynamics. We found that GCR1 has more similarities to class A and class S GPCRs than was previously acknowledged and further support evidence that GCR1 is a GPCR. Consequently, using the class A - GCR1 - class B alignment, we have produced active and inactive homology models of the CGRP receptor, a prototypical class B GPCR. In conjunction with mutation data, these models were used to identify a number of distinct class B motifs and their class A equivalents for the first time. Finally, molecular dynamic simulations were used to further confirm the role of the class B motifs.
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5

Henne, Randal Marlow. "Computational studies of G-protein coupled receptors /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/8048.

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6

Duong, Chi-Hong. "Approches statistiques en pharmacoépidémiologie pour la prise en compte des facteurs de confusion indirectement mesurés dans les bases de données médico-administratives : Application aux médicaments pris au cours de la grossesse." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASR028.

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Les bases de données médico-administratives sont de plus en plus utilisées en pharmacoépidémiologie. Néanmoins, l'existence de facteurs de confusion (FDC) non mesurés et non pris en compte peut biaiser les analyses. Dans ce travail, nous explorons l'intérêt d'exploiter la richesse des données avec la sélection à large échelle d'un grand nombre de covariables mesurées corrélées avec d'éventuels facteurs manquants pour les ajuster indirectement. Ce concept est à la base du score de propension en grande dimension (hdPS), et nous appliquons la même démarche à la G-computation (GC) et l'estimation Ciblée par Maximum de Vraisemblance (TMLE). Bien que ces méthodes aient été évaluées dans certaines études de simulation, leurs performances sur de grandes bases de données réelles restent peu étudiées. Cette thèse vise à évaluer leurs contributions à l'atténuation de l'effet de FDC directement ou indirectement mesurés dans le système national des données de santé (SNDS) pour des études de pharmacoépidémiologie chez la femme enceinte. Dans le chapitre 2, nous avons utilisé un ensemble de médicaments de référence en lien avec la prématurité pour comparer les performances des trois méthodes. Toutes ont diminué le biais de confusion, la GC donnant les meilleures performances. Dans le chapitre 3, nous avons réalisé une analyse par hdPS dans un contexte de modélisation plus complexe pour étudier le lien controversé entre les anti-inflammatoires non stéroïdiens (AINS) et la fausse couche spontanée (FCS). Nous avons implémenté un modèle de Cox avec variable dépendant du temps et l'approche “lag-time” visant à corriger d'autres biais (biais de temps immortel et biais protopathique). Nous avons comparé des analyses basées sur les facteurs d'ajustement choisis selon la littérature actuelle ou avec le hdPS. Dans ces deux types d'analyse, les AINS étaient associés à un surrisque de FCS, les différences observées dans les risques estimés pouvant s'expliquer en partie par la différence entre les estimands théoriques ciblés par les approches. Nos travaux permettent de confirmer la contribution des méthodes statistiques à atténuer le biais de confusion. Ils soulignent aussi des difficultés majeures rencontrées lors de leur application en pratique en lien avec la complexité de la modélisation et du plan d'étude, ainsi qu'avec leur coût computationnel
Healthcare administrative databases are increasingly used in pharmacoepidemiology. However, the existence of unmeasured and uncontrolled confounders can bias analyses. In this work, we explore the value of leveraging the richness of data through large-scale selection of a large number of measured covariates correlated with unmeasured confounders to indirectly adjust for them. This concept is the cornerstone of the High-dimensional propensity score (hdPS), and we apply the same approach to G-computation (GC) and Targeted Maximum Likelihood Estimation (TMLE). Although these methods have been evaluated in some simulation studies, their performance on large real-world databases remains underexplored. This thesis aims to assess their contributions to mitigating the effect of directly or indirectly measured confounders in the French administrative health care database (SNDS) for pharmacoepidemiological studies in pregnant women. In Chapter 2, we used a set of reference drugs related to prematurity to compare the performance of the three methods. All reduced confounding bias, with GC showing the best performance. In Chapter 3, we conducted an hdPS analysis in a more complex modeling setting to investigate the controversial association between non-steroidal anti-inflammatory drugs (NSAIDs) and miscarriage. We implemented a Cox model with time-dependent variables and the “lag-time” approach to address other biases (immortal time bias and protopathic bias). We compared analyses adjusted for factors chosen according to the current literature with those chosen by the hdPS algorithm. In both types of analysis, NSAIDs were associated with an increased risk of miscarriage, and the observed differences in estimated risks could partly be explained by the difference between the causal estimands targeted by the approaches. Our work confirms the contribution of statistical methods to reducing confounding bias. It also highlights major challenges encountered during their practical application, related to the complexity of modeling and study design, as well as their computational cost
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7

Simpson, Lisa Marie. "Computational studies of G protein-coupled receptor activation." Thesis, University of Essex, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.520117.

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8

Heo, Jiyoung Beauchamp Jesse L. "Computational studies of orphan G protein-coupled receptors /." Diss., Pasadena, Calif. : California Institute of Technology, 2007. http://resolver.caltech.edu/CaltechETD:etd-11102006-144154.

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9

Dilner, David. "Profitability = f(G) : Computational Thermodynamics, Materials Design and Process Optimization." Doctoral thesis, KTH, Materialvetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191243.

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The thesis starts by giving a motivation to materials modeling as a way to increase profitability but also a possibility decrease the environmental impact. Fundamental concepts of relevance for this work are introduced, this include the materials genome, ICME and of course the CALPHAD method. As a demonstration promising results obtained by an ICME approach using genetic algorithms and CALPHAD on the vacuum degassing process are presented. In order to make good predictive calculations and process models it is important to have good thermodynamic descriptions. Thus most part of the work has concerned the thermodynamic assessments of systems of importance for steelmaking, corrosion and similar processes. The main focus has been the assessment of sulfur-containing systems and thermodynamic descriptions of the Fe-Mn-Ca-Mg-S, Fe-Ca-O-S, Fe-Mg-O and Mg-Mn-O systems are presented. In addition, heat capacity measurements of relevance for the Mg-Mn-O system have been performed. To summarize the efforts some application examples concerning thermodynamic calculations related to steelmaking and inclusion formation are shown.

QC 20160829


COMPASS
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10

Baragatti, Meïli. "Sélection bayésienne de variables et méthodes de type Parallel Tempering avec et sans vraisemblance." Thesis, Aix-Marseille 2, 2011. http://www.theses.fr/2011AIX22100/document.

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Cette thèse se décompose en deux parties. Dans un premier temps nous nous intéressons à la sélection bayésienne de variables dans un modèle probit mixte.L'objectif est de développer une méthode pour sélectionner quelques variables pertinentes parmi plusieurs dizaines de milliers tout en prenant en compte le design d'une étude, et en particulier le fait que plusieurs jeux de données soient fusionnés. Le modèle de régression probit mixte utilisé fait partie d'un modèle bayésien hiérarchique plus large et le jeu de données est considéré comme un effet aléatoire. Cette méthode est une extension de la méthode de Lee et al. (2003). La première étape consiste à spécifier le modèle ainsi que les distributions a priori, avec notamment l'utilisation de l'a priori conventionnel de Zellner (g-prior) pour le vecteur des coefficients associé aux effets fixes (Zellner, 1986). Dans une seconde étape, nous utilisons un algorithme Metropolis-within-Gibbs couplé à la grouping (ou blocking) technique de Liu (1994) afin de surmonter certaines difficultés d'échantillonnage. Ce choix a des avantages théoriques et computationnels. La méthode développée est appliquée à des jeux de données microarray sur le cancer du sein. Cependant elle a une limite : la matrice de covariance utilisée dans le g-prior doit nécessairement être inversible. Or il y a deux cas pour lesquels cette matrice est singulière : lorsque le nombre de variables sélectionnées dépasse le nombre d'observations, ou lorsque des variables sont combinaisons linéaires d'autres variables. Nous proposons donc une modification de l'a priori de Zellner en y introduisant un paramètre de type ridge, ainsi qu'une manière de choisir les hyper-paramètres associés. L'a priori obtenu est un compromis entre le g-prior classique et l'a priori supposant l'indépendance des coefficients de régression, et se rapproche d'un a priori précédemment proposé par Gupta et Ibrahim (2007).Dans une seconde partie nous développons deux nouvelles méthodes MCMC basées sur des populations de chaînes. Dans le cas de modèles complexes ayant de nombreux paramètres, mais où la vraisemblance des données peut se calculer, l'algorithme Equi-Energy Sampler (EES) introduit par Kou et al. (2006) est apparemment plus efficace que l'algorithme classique du Parallel Tempering (PT) introduit par Geyer (1991). Cependant, il est difficile d'utilisation lorsqu'il est couplé avec un échantillonneur de Gibbs, et nécessite un stockage important de valeurs. Nous proposons un algorithme combinant le PT avec le principe d'échanges entre chaînes ayant des niveaux d'énergie similaires dans le même esprit que l'EES. Cette adaptation appelée Parallel Tempering with Equi-Energy Moves (PTEEM) conserve l'idée originale qui fait la force de l'algorithme EES tout en assurant de bonnes propriétés théoriques et une utilisation facile avec un échantillonneur de Gibbs.Enfin, dans certains cas complexes l'inférence peut être difficile car le calcul de la vraisemblance des données s'avère trop coûteux, voire impossible. De nombreuses méthodes sans vraisemblance ont été développées. Par analogie avec le Parallel Tempering, nous proposons une méthode appelée ABC-Parallel Tempering, basée sur la théorie des MCMC, utilisant une population de chaînes et permettant des échanges entre elles
This thesis is divided into two main parts. In the first part, we propose a Bayesian variable selection method for probit mixed models. The objective is to select few relevant variables among tens of thousands while taking into account the design of a study, and in particular the fact that several datasets are merged together. The probit mixed model used is considered as part of a larger hierarchical Bayesian model, and the dataset is introduced as a random effect. The proposed method extends a work of Lee et al. (2003). The first step is to specify the model and prior distributions. In particular, we use the g-prior of Zellner (1986) for the fixed regression coefficients. In a second step, we use a Metropolis-within-Gibbs algorithm combined with the grouping (or blocking) technique of Liu (1994). This choice has both theoritical and practical advantages. The method developed is applied to merged microarray datasets of patients with breast cancer. However, this method has a limit: the covariance matrix involved in the g-prior should not be singular. But there are two standard cases in which it is singular: if the number of observations is lower than the number of variables, or if some variables are linear combinations of others. In such situations we propose to modify the g-prior by introducing a ridge parameter, and a simple way to choose the associated hyper-parameters. The prior obtained is a compromise between the conditional independent case of the coefficient regressors and the automatic scaling advantage offered by the g-prior, and can be linked to the work of Gupta and Ibrahim (2007).In the second part, we develop two new population-based MCMC methods. In cases of complex models with several parameters, but whose likelihood can be computed, the Equi-Energy Sampler (EES) of Kou et al. (2006) seems to be more efficient than the Parallel Tempering (PT) algorithm introduced by Geyer (1991). However it is difficult to use in combination with a Gibbs sampler, and it necessitates increased storage. We propose an algorithm combining the PT with the principle of exchange moves between chains with same levels of energy, in the spirit of the EES. This adaptation which we are calling Parallel Tempering with Equi-Energy Move (PTEEM) keeps the original idea of the EES method while ensuring good theoretical properties and a practical use in combination with a Gibbs sampler.Then, in some complex models whose likelihood is analytically or computationally intractable, the inference can be difficult. Several likelihood-free methods (or Approximate Bayesian Computational Methods) have been developed. We propose a new algorithm, the Likelihood Free-Parallel Tempering, based on the MCMC theory and on a population of chains, by using an analogy with the Parallel Tempering algorithm
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11

Cárdenas, Domínguez Martha Ivón. "A computational intelligence analysis of G proteincoupled receptor sequinces for pharmacoproteomic applications." Doctoral thesis, Universitat Politècnica de Catalunya, 2017. http://hdl.handle.net/10803/458380.

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Arguably, drug research has contributed more to the progress of medicine during the past decades than any other scientific factor. One of the main areas of drug research is related to the analysis of proteins. The world of pharmacology is becoming increasingly dependent on the advances in the fields of genomics and proteomics. This dependency brings about the challenge of finding robust methods to analyze the complex data they generate. Such challenge invites us to go one step further than traditional statistics and resort to approaches under the conceptual umbrella of artificial intelligence, including machine learning (ML), statistical pattern recognition and soft computing methods. Sound statistical principles are essential to trust the evidence base built through the use of such approaches. Statistical ML methods are thus at the core of the current thesis. More than 50% of drugs currently available target only four key protein families, from which almost a 30% correspond to the G Protein-Coupled Receptors (GPCR) superfamily. This superfamily regulates the function of most cells in living organisms and is at the centre of the investigations reported in the current thesis. No much is known about the 3D structure of these proteins. Fortunately, plenty of information regarding their amino acid sequences is readily available. The automatic grouping and classification of GPCRs into families and these into subtypes based on sequence analysis may significantly contribute to ascertain the pharmaceutically relevant properties of this protein superfamily. There is no biologically-relevant manner of representing the symbolic sequences describing proteins using real-valued vectors. This does not preclude the possibility of analyzing them using principled methods. These may come, amongst others, from the field of statisticalML. Particularly, kernel methods can be used to this purpose. Moreover, the visualization of high-dimensional protein sequence data can be a key exploratory tool for finding meaningful information that might be obscured by their intrinsic complexity. That is why the objective of the research described in this thesis is twofold: first, the design of adequate visualization-oriented artificial intelligence-based methods for the analysis of GPCR sequential data, and second, the application of the developed methods in relevant pharmacoproteomic problems such as GPCR subtyping and protein alignment-free analysis.
Se podría decir que la investigación farmacológica ha desempeñado un papel predominante en el avance de la medicina a lo largo de las últimas décadas. Una de las áreas principales de investigación farmacológica es la relacionada con el estudio de proteínas. La farmacología depende cada vez más de los avances en genómica y proteómica, lo que conlleva el reto de diseñar métodos robustos para el análisis de los datos complejos que generan. Tal reto nos incita a ir más allá de la estadística tradicional para recurrir a enfoques dentro del campo de la inteligencia artificial, incluyendo el aprendizaje automático y el reconocimiento de patrones estadístico, entre otros. El uso de principios sólidos de teoría estadística es esencial para confiar en la base de evidencia obtenida mediante estos enfoques. Los métodos de aprendizaje automático estadístico son uno de los fundamentos de esta tesis. Más del 50% de los fármacos en uso hoy en día tienen como ¿diana¿ apenas cuatro familias clave de proteínas, de las que un 30% corresponden a la super-familia de los G-Protein Coupled Receptors (GPCR). Los GPCR regulan la funcionalidad de la mayoría de las células y son el objetivo central de la tesis. Se desconoce la estructura 3D de la mayoría de estas proteínas, pero, en cambio, hay mucha información disponible de sus secuencias de amino ácidos. El agrupamiento y clasificación automáticos de los GPCR en familias, y de éstas a su vez en subtipos, en base a sus secuencias, pueden contribuir de forma significativa a dilucidar aquellas de sus propiedades de interés farmacológico. No hay forma biológicamente relevante de representar las secuencias simbólicas de las proteínas mediante vectores reales. Esto no impide que se puedan analizar con métodos adecuados. Entre estos se cuentan las técnicas provenientes del aprendizaje automático estadístico y, en particular, los métodos kernel. Por otro lado, la visualización de secuencias de proteínas de alta dimensionalidad puede ser una herramienta clave para la exploración y análisis de las mismas. Es por ello que el objetivo central de la investigación descrita en esta tesis se puede desdoblar en dos grandes líneas: primero, el diseño de métodos centrados en la visualización y basados en la inteligencia artificial para el análisis de los datos secuenciales correspondientes a los GPCRs y, segundo, la aplicación de los métodos desarrollados a problemas de farmacoproteómica tales como la subtipificación de GPCRs y el análisis de proteinas no-alineadas.
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12

Vohra, Shabana. "Computational studies of class A and class B G protein-coupled receptors." Thesis, University of Essex, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.496278.

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13

Boukharta, Lars. "Computational Modelling of Ligand Complexes with G-Protein Coupled Receptors, Ion Channels and Enzymes." Doctoral thesis, Uppsala universitet, Beräknings- och systembiologi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-212103.

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Accurate predictions of binding free energies from computer simulations are an invaluable resource for understanding biochemical processes and drug action. The primary aim of the work described in the thesis was to predict and understand ligand binding to several proteins of major pharmaceutical importance using computational methods. We report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 G-protein coupled receptor and a series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones. Site-directed mutagenesis, homology modelling and docking were further used to characterize agonist binding to the human neuropeptide Y2 receptor, which is important in feeding behavior and an obesity drug target.  In a separate project, homology modelling was also used for rationalization of mutagenesis data for an integron integrase involved in antibiotic resistance. Blockade of the hERG potassium channel by various drug-like compounds, potentially causing serious cardiac side effects, is a major problem in drug development. We have used a homology model of hERG to conduct molecular docking experiments with a series of channel blockers, followed by molecular dynamics simulations of the complexes and evaluation of binding free energies with the linear interaction energy method. The calculations are in good agreement with experimental binding affinities and allow for a rationalization of three-dimensional structure-activity relationships with implications for design of new compounds. Docking, scoring, molecular dynamics, and the linear interaction energy method were also used to predict binding modes and affinities for a large set of inhibitors to HIV-1 reverse transcriptase. Good agreement with experiment was found and the work provides a validation of the methodology as a powerful tool in structure-based drug design. It is also easily scalable for higher throughput of compounds.
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Kumar, Subramanian Arun. "Computational studies of stabilisation of DNA Holliday junctions and G-Quadruplexes by novel daca analogues." Thesis, University of Reading, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.515805.

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15

Culka, Martin [Verfasser], and G. Matthias [Akademischer Betreuer] Ullmann. "Computational Modeling of Enzyme Reactions Involved in Aromatic Compound Metabolism / Martin Culka ; Betreuer: G. Matthias Ullmann." Bayreuth : Universität Bayreuth, 2017. http://d-nb.info/1147479453/34.

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16

Ongaro, Alberto. "TARGETING G-QUADRUPLEX DNA: SYNTHESIS OF NEW LIGANDS GUIDED BY ESI MASS SPECTROMETRY AND COMPUTATIONAL METHODS." Doctoral thesis, Università degli studi di Brescia, 2022. http://hdl.handle.net/11379/551760.

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La ricerca di nuove molecole in grado di legare il DNA a doppio filamento rappresenta un importante obbiettivo per il campo della chimica farmaceutica e potrebbe potenzialmente consentire di espandere il set di farmaci usati come cura per diverse patologie tra cui il cancro. Similarmente, l’identificazione di nuovi leganti selettivi per la struttura del DNA di tipo quadruplex può rappresentare un’interessante strategia alternativa per bersagliare l’acido nucleico nella sua forma non canonica. Inoltre i quadruplex sono presenti in specifiche regioni dei cromosomi chiamati telomeri, il cui mantenimento risulta cruciale per la vasta maggioranza dei tumori (J. W. Shay, W. E. Wright, Nature Reviews Genetics, 2019). Negli ultimi 30 anni, diversi ligandi sono stati sviluppati ed investigati per la loro capacità di stabilizzare il quadruplex; inoltre l’evoluzione nello studio strutturale ha portato alla scoperta di importanti tecniche analitiche ed investigative in grado di consentire lo studio sia della struttura stessa del quadruplex, che è ad oggi risaputo poter assumere diverse topologie, sia dell’interazione con esso di specifici ligandi. In questo contesto, la spettrometria di massa ESI in condizioni native è emersa come un potente strumento per analizzare importanti parametri del binding come la forza dell’interazione e la sua stechiometria. Inoltre l’uso di strumenti computazionali come il molecular docking e la molecular dynamics ha consentito, con un crescente grado di confidenza, la predizione della struttura finale dei complessi (Ribaudo et al., J Med Chem, 2021). In questa tesi di dottorato verrà presentato il lavoro di ricerca da me condotto durante questi tre anni per lo sviluppo di nuovi ligandi capaci di interagire con il DNA telomerico, sia nella sua forma a doppio filamento e ancor più nella sua forma non-canonica di tipo quadruplex. Nello specifico, i tre lavori presentati comprendono la sintesi di diversi ligandi, la loro caratterizzazione e lo studio dell’interazione con l’acido nucleico attraverso tecniche spettroscopiche e spettrometriche ed indagini di tipo computazionale. Nei primi due studi verrà discusso lo studio di ligandi mono- e di-sostituiti del DNA a doppio filamento e di tipo quadruplex, basati sulla struttura di tipo antracene-propargilammina. In particolare, un set di 6 ligandi sintetizzati attraverso la reazione di A3 coupling, hanno dimostrato una buona abilità di interagire con l’acido nucleico ma senza selettività per la struttura quadruplex (Ongaro et al., Chemistry Select, 2019). Per questo motivo la struttura è stata oggetto di ottimizzazione attraverso l’aggiunta di una seconda catena laterale, aumentando sia l’affinità che la selettività per il DNA di tipo quadruplex (Ribaudo et al., Molbank, 2020). Nel terzo studio riportato (Ongaro et al., ChemMedChem, 2021), la discussione si è invece focalizzata sui ligandi a struttura di tipo coniugato antrachinone-amminoacido, nello specifico 7 coniugati sono stati preparati usando l’efficace reazione di cicloaddizione CuAAC. Questi ultimi hanno dimostrato una elevata affinità e selettività per il DNA di tipo quadruplex ed inoltre l’abilità di indurre una variazione di topologia dello stesso.
The search for novel molecules able to bind to the double strand DNA is an important topic in the medicinal chemistry field and could help therefore to expand the set of drugs used against various diseases including cancer. Similarly, the identification of new selective quadruplex ligands, represents an appealing, alternative strategy, to target the nucleic acid when folded in this non-canonical form. Moreover, the quadruplexes can be found in a specific region of the chromosomes called telomeres, which maintenance is crucial for the vast majority of tumors (J. W. Shay, W. E. Wright, Nature Reviews Genetics, 2019). In these last 30 years, various scaffolds were developed and investigated for the stabilization of the quadruplex motif; also the evolution in the study of its structure led to the discovery of important techniques to investigate either the quadruplex arrangement itself, which is nowadays known to assume different forms, namely topologies, and also the ligand binding event. In this context, the native ESI mass spectrometry emerged as a compelling tool to evaluate relevant parameters as the interaction strength and the binding stoichiometry. Furthermore, the use of computational tools such as molecular docking and molecular dynamics, allowed the prediction of the final structure of the complexes with an increasing degree of confidence (Ribaudo et al., J Med Chem, 2021). In this doctoral thesis it will be presented the research work that I have conducted during these three last years on the development of new ligands able to target the telomeric DNA, either in its double strand form and even more in its non-canonical quadruplex fold. In the specific, the three works presented included the synthesis of different ligands, their characterization and the study of the interaction with the nucleic acid through spectrometric, spectroscopic techniques and computational investigations. In the first two studies, the investigation on mono- and di-substituted double strand DNA and quadruplex ligands based on the anthracene-propargylamine scaffold is discussed. In particular, a first set of 6 ligands, synthesized through the A3 coupling, demonstrated a good ability to interact with the nucleic acid but didn’t show a selectivity for the quadruplex fold (Ongaro et al., Chemistry Select, 2019). For this reason, the scaffold was optimized with the addition of a second side-chain, increasing both the affinity and the selectivity for the quadruplex DNA (Ribaudo et al., Molbank, 2020). In the third presented study (Ongaro et al., ChemMedChem, 2021), the discussion is focus instead on the anthraquinone-amino acid conjugate scaffold, prepared leveraging the CuAAC reaction which allowed an efficient generation of a set of 7 conjugates. The ligands demonstrated an elevated affinity and selectivity for the quadruplex DNA and the ability to induce a variation of the fold topology.
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17

Bornheimer, Scott Joseph. "Spatial and temporal regulation of G-protein signaling elucidated by computational modeling and live cell FRET imaging." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p3308008.

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Thesis (Ph. D.)--University of California, San Diego, 2008.
Title from first page of PDF file (viewed June 12, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.
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Melo, Diogo Amaral Rebouças. "Evolução morfológica e modularidade." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/41/41131/tde-21012013-150903/.

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Sistemas morfológicos quantitativos são descritos por medidas contínuas. A relação genética entre essas características dos indivíduos é representada pela matriz de covariância genética aditiva, a matriz G. Entender a evolução da matriz G, portanto, é de suma importância para compreender os padrões de diversificação encontrados na natureza. Neste trabalho estudamos modelos computacionais para a evolução de traços contínuos em populações naturais, sujeitas a variados tipos de seleção e condições internas, focando no problema da evolução dos padrões de integração e modularidade nessas populações. Testamos dois modelos com diferentes combinações de parâmetros em sua capacidade de reproduzir e elucidar padrões naturais. Seleção direcional correlacionada se mostrou uma força importante na criação desses padrões de covariação e a seleção estabilizadora correlacionada se mostrou fundamental para a manutenção desses padrões
Quantitative morphological systems are described by continuous measurements. The genetic relation between these characteristics of the individuals is represented by the genetic additive co-variance matrix, the G matrix. Understanding the evolution of the G matrix is, therefore, of paramount importance for proper interpretation of the patterns of diversification we observe in nature. In this work we study computational models for the evolution of quantitative traits in natural populations, subject to different natural selection and internal conditions, focusing on the problem of the evolution of the pattern of morphological integration and modularity. We test two models with different sets of parameters in their ability to reproduce and elucidate natural patterns. Directional correlated selection was necessary for the shaping of the patterns of morphological integration, and correlated stabilizing selection was fundamental to the maintenance of these patterns
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Gusmao, Eduardo G. Verfasser], Thomas [Akademischer Betreuer] Berlage, Martin [Akademischer Betreuer] Zenke, and Stefan [Akademischer Betreuer] [Decker. "Computational footprinting methods for next-generation sequencing experiments / Eduardo G. Gusmao ; Thomas Berlage, Martin Zenke, Stefan Josef Decker." Aachen : Universitätsbibliothek der RWTH Aachen, 2016. http://d-nb.info/1130871738/34.

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20

Nilsson, Lock Gun Antonia Evelina. "Mutational and computational characterization of transmembrane domains in the fungal G protein-coupled pheromone receptors STE2 and Mam2." Thesis, University of Warwick, 2011. http://wrap.warwick.ac.uk/50223/.

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G protein-coupled receptors (GPCRs) comprise the largest family of cell-surface receptors involved in sensing a multitude of ligands and are consequently attractive pharmacological targets. Their study is complicated by cross-talk between signalling pathways and altered receptor pharmacology due to, for instance, receptor oligomerization. Difficulties in obtaining structural information of the receptors hinder the understanding of oligomerization and therefore it is desirable to develop alternative approaches in which to study this phenomenon. The fungal pheromone GPCRs, STE2 and Mam2, from Saccharomyces cerevisiae and Schizosaccharomyces pombe respectively are both known to oligomerize and a GxxxG motif in the first transmembrane (TM) domain of STE2 has previously been shown to mediate receptor oligomerization. Previous work on polytopic proteins suggest that individual TM helices may be treated as individually stable domains, and it may therefore be possible to study oligomerization via single TM peptides as opposed to full-length receptor. This thesis describes the use of STE2 and Mam2 to explore TM helix oligomerization and the effects of mutations on receptor trafficking, localization and cellular signalling. The development of a luminescent reporter assay for Sz. pombe, which proved more sensitive than previously used assays and is capable of generating high-throughput data, is also discussed. It was found that STE2 could couple to the Sz. pombe pheromone-response pathway and mutations in the GxxxG dimerization motif affected both signalling and trafficking. Expression of the first TM GxxxG containing domain of STE2 was insufficient for oligomerization, in line with previous reports suggesting that the presence of the second domain is required for receptor oligomerization. In Mam2, a motif was identified that appeared homologous to the STE2 dimerization motif and mutations of this motif also affected trafficking and signalling. This domain could oligomerize in isolation, and mutations of the motif abolished oligomerization. In contrast the study of more polar TM domains appeared more complicated. These findings suggest that relatively hydrophobic TM domains can be studied as individually stable units, whereas more polar domains may require the presence of other TM domains.
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Gusmao, Eduardo Gade [Verfasser], Thomas Akademischer Betreuer] Berlage, Martin [Akademischer Betreuer] Zenke, and Stefan [Akademischer Betreuer] [Decker. "Computational footprinting methods for next-generation sequencing experiments / Eduardo G. Gusmao ; Thomas Berlage, Martin Zenke, Stefan Josef Decker." Aachen : Universitätsbibliothek der RWTH Aachen, 2016. http://d-nb.info/1130871738/34.

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22

Klemens, Fabian [Verfasser], and G. [Akademischer Betreuer] Thäter. "Combining computational fluid dynamics and magnetic resonance imaging data using lattice Boltzmann based topology optimisation / Fabian Klemens ; Betreuer: G. Thäter." Karlsruhe : KIT-Bibliothek, 2020. http://d-nb.info/1221186922/34.

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23

Rozycki, Torsten von [Verfasser], D. H. [Akademischer Betreuer] Nies, G. J. [Akademischer Betreuer] Krauss, and M. H. [Akademischer Betreuer] Saier. "Computational investigations of divalent heavy metal ion homeostasis / Torsten von Rozycki. Betreuer: D. H. Nies ; G. J. Krauss ; M. H. Saier." Halle, Saale : Universitäts- und Landesbibliothek Sachsen-Anhalt, 2009. http://d-nb.info/1024859924/34.

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24

Seelig, Stefan [Verfasser], Ralf [Akademischer Betreuer] Engbert, Sarah [Akademischer Betreuer] Risse, Ralf [Gutachter] Engbert, and Ronan G. [Gutachter] Reilly. "Parafoveal processing of lexical information during reading : from experiments to computational modeling / Stefan Seelig ; Gutachter: Ralf Engbert, Ronan G. Reilly ; Ralf Engbert, Sarah Risse." Potsdam : Universität Potsdam, 2021. http://d-nb.info/1236786459/34.

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25

Tinkl, Susanna [Verfasser], Wolfgang A. [Akademischer Betreuer] Wall, Christian G. H. [Akademischer Betreuer] Reeps, and Michael W. [Akademischer Betreuer] Gee. "Towards a predictive computational growth model for aneurysms / Susanna Tinkl. Betreuer: Wolfgang A. Wall. Gutachter: Wolfgang A. Wall ; Christian G. H. Reeps ; Michael W. Gee." München : Universitätsbibliothek der TU München, 2015. http://d-nb.info/1091562091/34.

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26

Tinkl, Susanna Sabine [Verfasser], Wolfgang A. [Akademischer Betreuer] Wall, Christian G. H. [Akademischer Betreuer] Reeps, and Michael W. [Akademischer Betreuer] Gee. "Towards a predictive computational growth model for aneurysms / Susanna Tinkl. Betreuer: Wolfgang A. Wall. Gutachter: Wolfgang A. Wall ; Christian G. H. Reeps ; Michael W. Gee." München : Universitätsbibliothek der TU München, 2015. http://nbn-resolving.de/urn:nbn:de:bvb:91-diss-20161209-1230842-1-0.

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27

Li, Weiyi. "Protein Engineering Hydrophobic Core Residues of Computationally Designed Protein G and Single-Chain Rop: Investigating the Relationship between Protein Primary structure and Protein Stability through High-Throughput Approaches." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398956266.

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28

Bahena, Silvia. "Computational Methods for the structural and dynamical understanding of GPCR-RAMP interactions." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-416790.

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Protein-protein interaction dominates all major biology processes in living cells. Recent studies suggestthat the surface expression and activity of G protein-coupled receptors (GPCRs), which are the largestfamily of receptors in human cells, can be modulated by receptor activity–modifying proteins (RAMPs). Computational tools are essential to complement experimental approaches for the understanding ofmolecular activity of living cells and molecular dynamics simulations are well suited to providemolecular details of proteins function and structure. The classical atom-level molecular modeling ofbiological systems is limited to small systems and short time scales. Therefore, its application iscomplicated for systems such as protein-protein interaction in cell-surface membrane. For this reason, coarse-grained (CG) models have become widely used and they represent an importantstep in the study of large biomolecular systems. CG models are computationally more effective becausethey simplify the complexity of the protein structure allowing simulations to have longer timescales. The aim of this degree project was to determine if the applications of coarse-grained molecularsimulations were suitable for the understanding of the dynamics and structural basis of the GPCRRAMP interactions in a membrane environment. Results indicate that the study of protein-proteininteractions using CG needs further improvement with a more accurate parameterization that will allowthe study of complex systems.
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Schroeder, Philipp W. [Verfasser], Gert [Akademischer Betreuer] Lube, Gert [Gutachter] Lube, Andreas [Gutachter] Dillmann, and Leo G. [Gutachter] Rebholz. "Robustness of High-Order Divergence-Free Finite Element Methods for Incompressible Computational Fluid Dynamics / Philipp W. Schroeder ; Gutachter: Gert, Lube; Andreas, Dillmann; Leo G., Rebholz ; Betreuer: Gert, Lube." Göttingen : Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2019. http://d-nb.info/1180026489/34.

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30

Mahajan, Rahul. "Gβγ acts at an inter-subunit cleft to activate GIRK1 channels." VCU Scholars Compass, 2012. http://scholarscompass.vcu.edu/etd/3307.

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Heterotrimeric guanine nucleotide-binding proteins (G-proteins) consist of an alpha subunit (Gα) and the dimeric beta-gamma subunit (Gβγ). The first example of direct cell signaling by Gβγ was the discovery of its role in activating G-protein regulated inwardly rectifying K+ (GIRK) channels which underlie the acetylcholine-induced K+ current responsible for vagal inhibition of heart rate. Published crystal structures have provided important insights into the structures of the G-protein subunits and GIRK channels separately, but co-crystals of the channel and Gβγ together remain elusive and no specific reciprocal residue interactions between the two proteins are currently known. Given the absence of direct structural evidence, we attempted to identify these functionally important channel-Gβγ interactions using a computational approach. We developed a multistage computational docking algorithm that combines several known methods in protein-protein docking. Application of the docking protocol to previously published structures of Gβγ and GIRK1 homomeric channels produced a clear signal of a favored binding mode. Analysis of this binding mode suggested a mechanism by which Gβγ promotes the open state of the channel. The channel-Gβγ interactions predicted by the model in silico could be disrupted in vitro by mutation of one protein and rescued by additional mutation of reciprocal residues in the other protein. These interactions were found to extend to agonist induced activation of the channels as well as to activation of the native heteromeric channels. Currently, the structural mechanism by which Gβγ regulates the functional conformations of GIRK channels or of any of its membrane-associated effector proteins is not known. This work shows the first evidence for specific reciprocal interactions between Gβγ and a GIRK channel and places these interactions in the context of a general model of intracellular regulation of GIRK gating.
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31

Chen, Sih-Yu. "Computational studies of biomolecules." Thesis, University of St Andrews, 2017. http://hdl.handle.net/10023/11064.

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In modern drug discovery, lead discovery is a term used to describe the overall process from hit discovery to lead optimisation, with the goal being to identify drug candidates. This can be greatly facilitated by the use of computer-aided (or in silico) techniques, which can reduce experimentation costs along the drug discovery pipeline. The range of relevant techniques include: molecular modelling to obtain structural information, molecular dynamics (which will be covered in Chapter 2), activity or property prediction by means of quantitative structure activity/property models (QSAR/QSPR), where machine learning techniques are introduced (to be covered in Chapter 1) and quantum chemistry, used to explain chemical structure, properties and reactivity. This thesis is divided into five parts. Chapter 1 starts with an outline of the early stages of drug discovery; introducing the use of virtual screening for hit and lead identification. Such approaches may roughly be divided into structure-based (docking, by far the most often referred to) and ligand-based, leading to a set of promising compounds for further evaluation. Then, the use of machine learning techniques, the issue of which will be frequently encountered, followed by a brief review of the "no free lunch" theorem, that describes how no learning algorithm can perform optimally on all problems. This implies that validation of predictive accuracy in multiple models is required for optimal model selection. As the dimensionality of the feature space increases, the issue referred to as "the curse of dimensionality" becomes a challenge. In closing, the last sections focus on supervised classification Random Forests. Computer-based analyses are an integral part of drug discovery. Chapter 2 begins with discussions of molecular docking; including strategies incorporating protein flexibility at global and local levels, then a specific focus on an automated docking program – AutoDock, which uses a Lamarckian genetic algorithm and empirical binding free energy function. In the second part of the chapter, a brief introduction of molecular dynamics will be given. Chapter 3 describes how we constructed a dataset of known binding sites with co-crystallised ligands, used to extract features characterising the structural and chemical properties of the binding pocket. A machine learning algorithm was adopted to create a three-way predictive model, capable of assigning each case to one of the classes (regular, orthosteric and allosteric) for in silico selection of allosteric sites, and by a feature selection algorithm (Gini) to rationalize the selection of important descriptors, most influential in classifying the binding pockets. In Chapter 4, we made use of structure-based virtual screening, and we focused on docking a fluorescent sensor to a non-canonical DNA quadruplex structure. The preferred binding poses, binding site, and the interactions are scored, followed by application of an ONIOM model to re-score the binding poses of some DNA-ligand complexes, focusing on only the best pose (with the lowest binding energy) from AutoDock. The use of a pre-generated conformational ensemble using MD to account for the receptors' flexibility followed by docking methods are termed “relaxed complex” schemes. Chapter 5 concerns the BLUF domain photocycle. We will be focused on conformational preference of some critical residues in the flavin binding site after a charge redistribution has been introduced. This work provides another activation model to address controversial features of the BLUF domain.
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Ma, Yingfang. "Electronic Structure, Optical Properties and Long-Range-Interaction Driven Mesoscale Assembly." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1497049273517057.

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33

Favara, David M. "The biology of ELTD1/ADGRL4 : a novel regulator of tumour angiogenesis." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:0d00af0a-bb43-44bc-ba0b-1f8acbe34bc5.

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Background: Our laboratory identified ELTD1, an orphan GPCR belonging to the adhesion GPCR family (aGPCR), as a novel regulator of angiogenesis and a potential anti-cancer therapeutic target. ELTD1 is normally expressed in both endothelial cells and vascular smooth muscle cells and expression is significantly increased in the tumour vasculature. The aim of this project was to analyse ELTD1's function in endothelial cells and its role in breast cancer. Method: 62 sequenced vertebrate genomes were interrogated for ELTD1 conservation and domain alterations. A phylogenetic timetree was assembled to establish time estimates for ELTD1's evolution. After ELTD1 silencing, mRNA array profiling was performed on primary human umbilical vein endothelial cells (HUVECs) and validated with qPCR and confocal microscopy. ELTD1's signalling was investigated by applying the aGPCR ‘Stinger/tethered-agonist Hypothesis'. For this, truncated forms of ELTD1 and peptides analogous to the proposed tethered agonist region were designed. FRET-based 2nd messenger (Cisbio IP-1;cAMP) and luciferase-reporter assays (NFAT; NFÎoB; SRE; SRF-RE; CREB) were performed to establish canonical GPCR activation. To further investigate ELTD1's role in endothelial cells, ELTD1 was stably overexpressed in HUVECS. Functional angiogenesis assays and mRNA array profiling were then performed. To investigate ELTD1 in breast cancer, a panel of cell lines representative of all molecular subtypes were screened using qPCR. Furthermore, an exploratory pilot study was performed on matched primary and regional nodal secondary breast cancers (n=43) which were stained for ELTD1 expression. Staining intensity was then scored and compared with relapse free survival and overall survival. Results: ELTD1 arose 435 million years ago (mya) in bony fish and is present in all subsequent vertebrates. ELTD1 has 3 evolutionary variants of which 2 are most common: one variant with 3 EGFs and a variant with 2 EGFs. Additionally, ELTD1 may be ancestral to members of aGPCR family 2. HUVEC mRNA expression profiling after ELTD1 silencing showed upregulation of the mitochondrial citrate transporter SLC25A1, and ACLY which converts cytoplasmic citrate to Acetyl CoA, feeding fatty acid and cholesterol synthesis, and acetylation. A review of lipid droplet (fatty acid and cholesterol) accumulation by confocal microscopy and flow cytometry (FACS) revealed no changes with ELTD1 silencing. Silencing was also shown to affect the Notch pathway (downregulating the Notch ligand JAG1 and target gene HES2; upregulating the Notch ligand DLL4) and inducing KIT, a mediator of haematopoietic (HSC) and endothelial stem cell (ESC) maintenance. Signalling experiments revealed that unlike other aGPCRs, ELTD1 does not couple to any canonical GPCR pathways (Gαi, Gαs, Gαq, Gα12/13). ELTD1 overexpression in HUVECS revealed that ELTD1 induces an endothelial tip cell phenotype by promoting sprouting and capillary formation, inhibiting lumen anastomoses in mature vessels and lowering proliferation rate. There was no effect on wound healing or adhesion to angiogenesis associated matrix components. Gene expression changes following ELTD1 overexpression included upregulation of angiogenesis associated ANTRX1 as well as JAG1 and downregulation of migration associated CCL15 as well as KIT and DLL4. In breast cancer, none of the representative breast cancer cell lines screened expressed ELTD1. ELTD1 breast cancer immunohistochemistry revealed higher levels of vascular ELTD1 staining intensity within the tumour stroma contrasted to normal stroma and expression within tumour epithelial cells. Additionally, ELTD1 expression in tumour vessels was differentially expressed between the primary breast cancer microenvironment and that of the matched regional node. Due to the small size of the pilot study population, survival comparisons between the various subgroups did not yield significant results. Conclusion: ELTD1 is a novel regulator of endothelial metabolism through its suppression of ACLY and the related citrate transporter SLC25A1. ELTD1 also represses KIT, which is known to mediate haematopoietic and endothelial progenitors stem cell maintenance, a possible mechanism through which endothelial cells maintain terminal endothelial differentiation. ELTD1 does not signal like other adhesion GPCRS with CTF and FL forms of ELTD1 not signalling canonically. Additionally, ELTD1 regulates various functions of endothelial cell behaviour and function, inducing an endothelial tip cell phenotype and is highly evolutionarily conserved. Lastly, ELTD1 is differentially expressed in tumour vessels between primary breast cancer and regional nodal metastases and is also expressed in a small subset of breast cancer cells in vivo despite no cancer cell lines expressing ELTD1. The pilot study investigating ELTD1 in the primary breast cancer and regional involved nodes will be followed up with a larger study including the investigation of ELTD1 in distant metastases.
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Steinebach, Mario, Alexander Friebel, Christine Häckel-Riffler, Volker Tzschucke, Caroline Pollmer, Gabriela Horst, Antje Brabandt, and Kathrin Reichold. "TU-Spektrum 2/2004, Magazin der Technischen Universität Chemnitz." Universitätsbibliothek Chemnitz, 2004. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200401740.

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35

Chang, Sheng-Chih, and 張勝致. "The research of computation improvement on G.729’s fixed codebook." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/99q95n.

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碩士
國立臺北科技大學
電機工程系研究所
95
The computation improvement on G.729’s fixed codebook is researched and implemented. Moreover then 20% computation of G.729 is paid on the fixed codebook search. In this thesis, an preprocessing algorithm is employed to limit the search domain of fixed codebook’s space. In the experimental results, more than 98.54% of computation is reduced. The speech quality is still good in this approach. The MOS of original G.729 is 4.5 and the new approach is about 3.8. It is reasonable good and the performance of this approach is confirmed.
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陳建吉. "Computational Improvement for G.729 Standard." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/79305205596461365434.

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碩士
國立臺北科技大學
電機工程系碩士班
91
The computational improvement on G.729 standard is studied in this thesis. Three algorithms are employed and proposed to enhance the computational performance of G.729. Firstly, the “TIE+PDE” algorithm is employed to reduce the VQ-based quantization of LSP parameter. More than 13.97% of computation is reduced. Secondly, the “WD-LSP” algorithm is proposed to reduce the computation of open-loop pitch. More than 23.69% of computation is reduced. Finally, the “NCPL” algorithm is proposed to reduce the search space of fixed codebook. More than 18.38% of computation is reduced. Finally, three algorithms are simultaneously applied, which result in a total reduction of 56.04% in computation, with a reasonable good quality of synthesized speech sound.
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Heo, Jiyoung. "Computational Studies of Orphan G Protein-Coupled Receptors." Thesis, 2007. https://thesis.library.caltech.edu/4497/1/00jheo-Title.pdf.

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G protein-coupled receptors (GPCRs) play an essential role in cell communications and sensory functions. Consequently, they are involved in wide variety of diseases and are targets for many drug therapies. Particularly important is the large number of orphan GPCRs, which may play important, albeit unknown, functions in various cells. To understand their respective physiological roles, it is important to identify their endogenous ligands, and to find small molecule ligands that would serve as selective agonists or antagonists. The mas-related gene G protein-coupled receptors (Mrg receptors) belong to the orphan GPCR family, which is expressed in a specific subset of sensory neurons known to detect painful stimuli, suggesting that they could be involved in pain sensation or modulation.

The primary focus of this thesis is to predict the 3D structure and binding site of Mrg receptors and to identify novel ligands that would be potential agonists or antagonists. We predict the 3D structure for the mouse MrgC11 (mMrgC11) and the binding site for five chiral FMRF-NH2 ligands. We correctly predict the relative binding observed for these five ligands. We find that Tyr110 (TM3), Asp161 (TM4), and Asp179 (TM5) are particularly important to binding the ligands. Subsequently, we carry out mutagenesis experiments followed by intracellular calcium release assays that demonstrate the dramatic decrease in activity for the Y110A, D161A, and D179A mutants predicted by our model.

The all-atom molecular dynamics simulation of the mMrgC11/F-(D)M-R-F-NH2 complex structure in explicit water and infinite lipid membrane system shows that some conformational fluctuations are present, but no significant instability is detected, thus validating our structure prediction method.

The virtual screening with the combination of QSPR and docking methods is carried out for the predicted mMrgC11 receptor. The compounds showing the antagonistic effect are identified by competitive functional assays. These hit compounds are certainly good staring points in designing better agonists or antagonists.

The binding site of rat MrgA receptor that shows differential binding between adenine and guanine is also predicted. The predicted binding affinity correlates with the availability of the hydrogen bonds to two Asn residues, which would be primary mutation candidates to validate the structure.

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38

Zhuo, Chang Zhi, and 卓長志. "Computational Reduction For G.729’s LSP Quantization." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/31560353809992208867.

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碩士
國立勤益科技大學
電機工程系
98
G.729 standard has been widely used in the VoIP system. But the computational complexity is too large to real-time work via software implementation on embedded devices. Even though the G.729A, it is still hard to implement. This paper will focus on the computational reduction of the quantization procedure of LSP coefficients. Thus, the hybrid two-stage VQ is proposed to replace the original structure. Experimental results confirm that more than 80% of computations can be eliminated in comparison with the conventional G.729 as well as the performance of speech quality is still good. The proposed approach can be successfully used in LSP quantization procedure and the efficiency is excellent.
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39

Han, Tsu-Fen, and 韓祖棻. "G-BLAST: a Grid-Based Solution for mpiBLAST on Computational Grids." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/34260613923261588347.

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碩士
東海大學
資訊工程與科學系
95
The research and development of bioinformatics (e.g., genomic sequence alignment) has been growing with each passing day in the past few years so that continue demands on large computing powers are required to support better performance. This trend requires usually solved by parallel computing techniques, because Cluster technology can reduce the execution time and increase genomic sequence alignment efficiency. For example, mpiBLAST is a parallel version of NCBI BLAST that combines the NCBI BLAST with Message Passing Interface standards. However, most laboratories can not build up powerful computing environments. They usually connect dozens or even hundreds of personal computers to build weak computing environments. Besides, Cluster usually is limited by a local computing environment that hinders the computing extendibility significantly. The concepts of the Grid framework are designated to overcome the aforementioned problems. Grid environments coordinate the resources of distributed virtual organizations and satisfy various computational demands for bioinformatics applications. In this thesis, we have deployed a BioGrid framework named G-BLAST. Currently, G-BLAST is designed for genomic sequence alignment by using the Grid environment and accessible mpiBLAST application, which is designed for Cluster environment, from a server node. G-BLAST is endowed with selection the most adaptive work nodes, dynamic fragmenting genomic database, and self-adjust performance data abilities. To enhance the capability and usability of G-BLAST, we also deployed a Grid Service Portal and a Grid Service GUI desk application for general users to submit jobs and for host administrators to maintain their own work nodes.
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40

Kirkpatrick, Andrea. "Computational Predictions of G Protein-Coupled Receptor Structures and Binding Sites." Thesis, 2015. https://thesis.library.caltech.edu/8820/1/Kirkpatrick_A_thesis.pdf.

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G protein-coupled receptors (GPCRs) are the largest family of proteins within the human genome. They consist of seven transmembrane (TM) helices, with a N-terminal region of varying length and structure on the extracellular side, and a C-terminus on the intracellular side. GPCRs are involved in transmitting extracellular signals to cells, and as such are crucial drug targets. Designing pharmaceuticals to target GPCRs is greatly aided by full-atom structural information of the proteins. In particular, the TM region of GPCRs is where small molecule ligands (much more bioavailable than peptide ligands) typically bind to the receptors. In recent years nearly thirty distinct GPCR TM regions have been crystallized. However, there are more than 1,000 GPCRs, leaving the vast majority of GPCRs with limited structural information. Additionally, GPCRs are known to exist in a myriad of conformational states in the body, rendering the static x-ray crystal structures an incomplete reflection of GPCR structures. In order to obtain an ensemble of GPCR structures, we have developed the GEnSeMBLE procedure to rapidly sample a large number of variations of GPCR helix rotations and tilts. The lowest energy GEnSeMBLE structures are then docked to small molecule ligands and optimized. The GPCR family consists of five subfamilies with little to no sequence homology between them: class A, B1, B2, C, and Frizzled/Taste2. Almost all of the GPCR crystal structures have been of class A GPCRs, and much is known about their conserved interactions and binding sites. In this work we particularly focus on class B1 GPCRs, and aim to understand that family’s interactions and binding sites both to small molecules and their native peptide ligands. Specifically, we predict the full atom structure and peptide binding site of the glucagon-like peptide receptor and the TM region and small molecule binding sites for eight other class B1 GPCRs: CALRL, CRFR1, GIPR, GLR, PACR, PTH1R, VIPR1, and VIPR2. Our class B1 work reveals multiple conserved interactions across the B1 subfamily as well as a consistent small molecule binding site centrally located in the TM bundle. Both the interactions and the binding sites are distinct from those seen in the more well-characterized class A GPCRs, and as such our work provides a strong starting point for drug design targeting class B1 proteins. We also predict the full structure of CXCR4 bound to a small molecule, a class A GPCR that was not closely related to any of the class A GPCRs at the time of the work.
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41

Lorkowski, Peter. "A System Architecture for the Monitoring of Continuous Phenomena by Sensor Data Streams." Doctoral thesis, 2019. https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-201903151252.

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The monitoring of continuous phenomena like temperature, air pollution, precipitation, soil moisture etc. is of growing importance. Decreasing costs for sensors and associated infrastructure increase the availability of observational data. These data can only rarely be used directly for analysis, but need to be interpolated to cover a region in space and/or time without gaps. So the objective of monitoring in a broader sense is to provide data about the observed phenomenon in such an enhanced form. Notwithstanding the improvements in information and communication technology, monitoring always has to function under limited resources, namely: number of sensors, number of observations, computational capacity, time, data bandwidth, and storage space. To best exploit those limited resources, a monitoring system needs to strive for efficiency concerning sampling, hardware, algorithms, parameters, and storage formats. In that regard, this work proposes and evaluates solutions for several problems associated with the monitoring of continuous phenomena. Synthetic random fields can serve as reference models on which monitoring can be simulated and exactly evaluated. For this purpose, a generator is introduced that can create such fields with arbitrary dynamism and resolution. For efficient sampling, an estimator for the minimum density of observations is derived from the extension and dynamism of the observed field. In order to adapt the interpolation to the given observations, a generic algorithm for the fitting of kriging parameters is set out. A sequential model merging algorithm based on the kriging variance is introduced to mitigate big workloads and also to support subsequent and seamless updates of real-time models by new observations. For efficient storage utilization, a compression method is suggested. It is designed for the specific structure of field observations and supports progressive decompression. The unlimited diversity of possible configurations of the features above calls for an integrated approach for systematic variation and evaluation. A generic tool for organizing and manipulating configurational elements in arbitrary complex hierarchical structures is proposed. Beside the root mean square error (RMSE) as crucial quality indicator, also the computational workload is quantified in a manner that allows an analytical estimation of execution time for different parallel environments. In summary, a powerful framework for the monitoring of continuous phenomena is outlined. With its tools for systematic variation and evaluation it supports continuous efficiency improvement.
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42

Othersen, Olaf G. [Verfasser]. "Inducers and induction of the tetracycline repressor protein : computational studies / vorgelegt von Olaf G. Othersen." 2007. http://d-nb.info/986220507/34.

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43

Niemer, Rachel K. "Computational Studies of the Structure and Function of Two Lipid-Activated G Protein-Coupled Receptors." Thesis, 2007. https://thesis.library.caltech.edu/2244/2/CH0.pdf.

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Phospholipids are pleiotropic intercellular signaling molecules that have been implicated in various pathologies, including tumorigenesis. Both lysophosphatidic acid (LPA) and sphingosine-1-phosphate (S1P), among other phospholipids, use G protein coupled receptors (GPCRs) to transduce extracellular signals. Other families of GPCRs have successfully been utilized by the pharmaceutical industry, and further understanding of the phospholipid-receptor interaction can highlight potential therapeutic targets in these signaling pathways.

This thesis presents research into the interaction between specific G protein-coupled receptors, lysophosphatidic acid receptor-2 (LPA2) and sphingosine-1-phosphate receptor 1 (S1P1), and their ligands, in an attempt to further validate our method of GPCR structure prediction and to understand subtype specificity within this family of lipid receptors. Although the first principles method of GPCR structure prediction has quite successfully predicted the protein structure of small molecule receptors, lipid receptors create a unique challenge. The surface area on the inside of a small molecule receptor contains a large percentage of polar groups, easily differentiating the inner surface from the highly hydrophobic outer surface. Lipid receptors do not show as dramatic a distinction, as the inner surface is significantly hydrophobic to bind the lipid ligand.

Herein we propose and test a new method of orienting the seven transmembrane helices of a GPCR relative to one another through an analysis of the lipid solubility of each residue in conjunction with an optimization of the inter-helical hydrogen bonding associations. We predict structures for LPA2 and S1P1 that replicate the relative binding of different lipids within the LPA and S1P lipid families. The interaction energies between the receptors and the tested ligands correlates well with ligand efficacy, and qualitative analysis of functional group-residue interactions further validates our model for both LPA2 an S1P.

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44

Bray, Jenelle Kiara. "The Development and Application of Computational Methods for the Prediction of G Protein-Coupled Receptor Structures." Thesis, 2010. https://thesis.library.caltech.edu/5278/1/thesis_jenelle_bray.pdf.

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Computational methods for the prediction of G protein-coupled receptor (GPCR) structures were applied to serotonin receptors, and new methods were developed to predict an orphan GPCR structure. First, the MembStruk procedure was used to predict the structures of the serotonin 2b and 2c receptors. Ligand binding sites for agonists and antagonists were predicted for both receptors. In addition, the SAR data for a series of psilocybin analogs bound to serotonin 2c were predicted. There was good agreement with binding and mutagenesis experiments.

A new structure prediction procedure called SuperBiHelix was developed to predict an ensemble of low-lying structures. SuperBiHelix samples the tilt and sweep angles of the transmembrane helices along with the rotation of the helices along the helical axes. The procedure was validated on the β2-adrenergic receptor and A2A adenosine receptor crystal structures. This procedure was then used to predict the structure of GPR88, an orphan receptor. GPR88 has been identified as a novel target for psychiatric disorders. Three lipids were predicted to bind to GPR88. The head group of a lipid would bind to R113(3) and R116(3) at the extracellular side of the receptor. The lipid tail would bind in an aliphatic pocket in the TM2-TM3-TM6-TM7 region. The predicted bound complexes offer good suggestions for binding and mutagenesis experiments that could help validate the proposed structures.

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45

Ludwig, Dorothea. "Methodenentwicklung zur GIS-gestützten Standortanalyse von Solaranlagen auf Grundlage hochauflösender Laserscandaten." Doctoral thesis, 2016. https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-2016030814307.

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Ziel der Arbeit ist die Methodenentwicklung zur Berechnung des Solarenergiepotenzials auf Dachflächen für sämtliche Gebäude eines großen Gebiets (Stadt, Landkreis) auf Grundlage von Laserscandaten. Die Methode zur Solarpotenzialberechnung wurde mit dem Hintergrund des notwendigen Handlungsbedarfs an Maßnahmen für den Klimaschutz entwickelt. Die Ausgabe des Solarpotenzials auf Dachflächen für alle Gebäude einer Verwaltungseinheit liefert flächendeckende und neutrale Informationen für den Bürger und die Verwaltung. Insbesondere die solare Nutzung auf den keiner Flächenkonkurrenz unterliegenden Dachflächen birgt enormes Potenzial und liefert einen wichtigen Beitrag zur Energiewende. Das Ergebnis dieser Arbeit präsentiert eine Methode, über die eine automatisierte Berechnung des Solarpotenzials auf Dachflächen auf Basis von Laserscandaten mit hoher Genauigkeitsausgabe für große Region realisierbar ist. Die Methode besteht aus sechs Prozessschritten. Es handelt sich um die Datenaufbereitung, die Selektion der homogenen Dachteilflächenbereiche, die Einstrahlungsanalyse, die Verschattungsableitung und die Berechnung des Solarpotenzials. Zudem wird eine Rohdatenkontrolle zur Qualitätsbewertung der Laserscandaten umgesetzt. Zentraler Verfahrensschritt ist die Ableitung der homogenen Dachteilflächen, die unter Berücksichtigung möglichst vieler auch kleiner Dachstrukturen gebildet werden. Das entwickelte Mehrfach-Thresholding Verfahren ermöglicht über die Auswertung der Dachneigung und Dachausrichtung die Separierung von planaren Dachteilflächen. Über den r.sun Algorithmus von GRASS GIS wird die Einstrahlungsanalyse umgesetzt, die den Sonnenstand über den Tag und das Jahr für den Betrachtungsort simuliert und die direkte, diffuse und Globalstrahlung auf die Dachfläche für unterschiedliche Zeitperioden ausgeben lässt. Die Jahressumme der Globalstrahlung wird für jede Dachteilfläche unter Ausschluss stark verschatteter Bereiche errechnet und dient als Grundlage für die Potenzialberechnung. Im Ergebnis enthält jedes Dachteilflächenpolygon Angaben zur geeigneten Modulfläche, zur Höhe der Globalstrahlung, zum potenziellen Stromertrag, zur potenziellen kW-Leistung und zur CO2-Einsparsumme. Datengrundlage sind Laserscandaten, die die Oberflächensituation mit sämtlichen Strukturen abbilden, sowie Gebäudeumringe aus den Liegenschaftsdaten zur Lokalisierung des Gebäudes beziehungsweise des Daches. Laserscandaten eignen sich, abhängig von der Qualität, sehr gut, um im Modell den Betrachtungs- und Einflussraum, der für die Ausgabe des Solarpotenzials auf Dachflächen wichtig ist, flächendeckend und realitätsnah abzubilden. Hier sind insbesondere das Dach insgesamt und die Dachstrukturen sowie die Vegetation, insbesondere Bäume und die Umgebungstopographie die wichtigen Elemente, die flächendeckend und in möglichst hoher Auflösung im Modell vorliegen und berücksichtigt werden sollen, da sie möglicherweise die ertragreiche und wirtschaftliche Nutzung einer Solaranalage verhindern. Über eine rasterbasierte Modellierung ermöglichen diese Daten die Berechnung der Standortparameter wie Dachneigung, Dachausrichtung, Verschattung, Einstrahlungsenergie und Dachflächengröße. An die Laserscandaten werden bestimmte qualitative Anforderungen gestellt, um eine Genauigkeit der Potenzialwerte zu garantieren. Das relativ junge Verfahren wurde in den vergangenen Jahren stark weiter entwickelt, die Lage- und Höhengenauigkeit und Punktdichte wurden deutlich erhöht. Zahlreiche Laserscandatensätze unterschiedlicher Qualität wurden ausgewertet. Die Arbeit beschreibt Mindestanforderungen an die Qualität der Daten, die für eine hohe Qualitätsausgabe des Solarpotenzials benötigt werden. Die Genauigkeit der Solarpotenzialergebnisse wurden über Gebäudepläne realer Objekte, Vor-Ort Messungen und Erträge von bestehenden PV-Anlagen evaluiert. Erzielbare Abweichungen von 2% in der Neigung und 1% in der Ausrichtung sind über die entwickelte Methode auf Grundlage von Laserscandaten mit ausreichender Qualität erreichbar. Größere Abweichungen mit 6% Prozent wurden bei der Dachflächengröße errechnet. Die Bewertung über Referenzanlagen und dessen spezifischem Stromertrag lieferte eine Abweichung von 1,2%. Die Evaluierungsergebnisse bestätigen den Methodenansatz und liefern gute Resultate in der Genauigkeit der Solarpotenzialwerte.
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46

Prakash, Hastagiri. "A Mechanism Design Approach To Resource Procurement In Computational Grids With Rational Resource Providers." Thesis, 2006. https://etd.iisc.ac.in/handle/2005/553.

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A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities. In the presence of grid users who are autonomous, rational, and intelligent, there is an overall degradation of the total efficiency of the computational grid in comparison to what can be achieved when the participating users are centrally coordinated . This loss in efficiency might arise due to an unwillingness on the part of some of the grid resource providers to either not perform completely or not perform to the fullest capability, the computational jobs of other users in the grid. In this thesis, our attention is focused on designing grid resource procurement mechanisms which a grid user can use for procuring resources in a computational grid based on bids submitted by autonomous, rational, and intelligent resource providers. Specifically, we follow a game theoretic and mechanism design approach to design three elegant, different incentive compatible procurement mechanisms for this purpose: G-DSIC (Grid-Dominant Strategy Incentive Compatible) mechanism which guarantees that truthful bidding is a best response for each resource provider, irrespective of what the other resource providers bid G-BIC (Grid-Bayesian Nash Incentive Compatible) mechanism which only guarantees that truthful bidding is a best response for each resource provider whenever all other resource providers also bid truthfully G-OPT (Grid-Optimal) mechanism which minimizes the cost to the grid user, satisfying at the same time, (1) Bayesian Incentive Compatibility (which guarantees that truthful bidding is a best response for each resource provider whenever all other resource providers also bid truthfully) and (2) Individual Rationality (which guarantees that the resource providers have non-negative payoffs if they participate in the bidding process). We evaluate the relative merits and demerits of the above three mechanisms using game theoretical analysis and numerical experiments. The mechanisms developed in this thesis are in the context of parameter sweep type of jobs, which consist of multiple homogeneous and independent tasks. We believe the use of the mechanisms proposed transcends beyond parameter sweep type of jobs and in general, the proposed mechanisms could be extended to provide a robust way of procuring resources in a computational grid where the resource providers exhibit rational and strategic behavior.
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47

Prakash, Hastagiri. "A Mechanism Design Approach To Resource Procurement In Computational Grids With Rational Resource Providers." Thesis, 2006. http://hdl.handle.net/2005/553.

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A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities. In the presence of grid users who are autonomous, rational, and intelligent, there is an overall degradation of the total efficiency of the computational grid in comparison to what can be achieved when the participating users are centrally coordinated . This loss in efficiency might arise due to an unwillingness on the part of some of the grid resource providers to either not perform completely or not perform to the fullest capability, the computational jobs of other users in the grid. In this thesis, our attention is focused on designing grid resource procurement mechanisms which a grid user can use for procuring resources in a computational grid based on bids submitted by autonomous, rational, and intelligent resource providers. Specifically, we follow a game theoretic and mechanism design approach to design three elegant, different incentive compatible procurement mechanisms for this purpose: G-DSIC (Grid-Dominant Strategy Incentive Compatible) mechanism which guarantees that truthful bidding is a best response for each resource provider, irrespective of what the other resource providers bid G-BIC (Grid-Bayesian Nash Incentive Compatible) mechanism which only guarantees that truthful bidding is a best response for each resource provider whenever all other resource providers also bid truthfully G-OPT (Grid-Optimal) mechanism which minimizes the cost to the grid user, satisfying at the same time, (1) Bayesian Incentive Compatibility (which guarantees that truthful bidding is a best response for each resource provider whenever all other resource providers also bid truthfully) and (2) Individual Rationality (which guarantees that the resource providers have non-negative payoffs if they participate in the bidding process). We evaluate the relative merits and demerits of the above three mechanisms using game theoretical analysis and numerical experiments. The mechanisms developed in this thesis are in the context of parameter sweep type of jobs, which consist of multiple homogeneous and independent tasks. We believe the use of the mechanisms proposed transcends beyond parameter sweep type of jobs and in general, the proposed mechanisms could be extended to provide a robust way of procuring resources in a computational grid where the resource providers exhibit rational and strategic behavior.
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48

Fraser, Naomi K. "Style in science fiction and fantasy: studies in stylometry." Thesis, 2018. http://hdl.handle.net/1959.13/1385736.

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Research Doctorate - Doctor of Philosophy (PhD)
This thesis explores style in science fiction and fantasy by applying stylometry to three case studies. These are genres that are traditionally analysed for the potency of their themes and tropes rather than for their language and style. In each case study, the multivariate method Principal Component Analysis (PCA) is applied as a data-reduction technique to corpora containing examples of science fiction and fantasy texts. The data-set analysed by PCA includes the proportional frequencies of no more than one hundred of the most common words in each corpus. As such, this thesis analyses the underlying style of texts through common words that are generally overlooked by readers but are ubiquitous and integral to the structure of language. Style is a multifarious term but is defined broadly in this thesis to mean patterned variation in the way language is used, often to artistic effect, such as in genres or between authors. By studying the base strata of style this thesis relates the function of underlying features in language to prominent features of texts and genres. The statistical study of style is presented in three case studies: the contextualisation of style in early science fiction and fantasy; the case of Olaf Stapledon’s style; and the stylistic variation across J.K. Rowling’s Harry Potter sequence (1997-2007). The first case study examines late-Victorian texts and asks how H.G. Wells and George MacDonald’s early science fiction and fantasy texts, The Time Machine (1895) and Lilith (1895) stylistically relate to contemporaneous works. The results indicate that Wells’s style is similar to adventure fiction while MacDonald’s fantasy, though it appears highly eccentric to the contemporary reader, does not stand out among peers. The second case study presents an argument for the effectiveness of the style of Olaf Stapledon through computational comparisons with his predecessor, H.G. Wells, and his modernist contemporary, Virginia Woolf. Although, Stapledon is considered a poor stylist and is celebrated on the basis of his visionary imagination rather than his storytelling prowess, the results indicate that his style is relatively distinctive but also consistent with his artistic goals. The third case study explores whether computational evidence can be found for underlying stylistic variation in Rowling’s Harry Potter sequence. The results are then compared with those from two other fantasy book series, C.S. Lewis’s Complete Chronicles of Narnia (1950-1956) and Diane Duane’s Young Wizards (1983-2016), in order to ascertain the nature of style in other series. The statistical results demonstrate progressive change in Rowling’s sequence occurring at a level previously unknown to critics. Together these three case studies offer new perspectives on the role of style in science fiction and fantasy through a computational method that has not previously been employed in relation to either genre.
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