Dissertations / Theses: 'Interactive graph visualization'

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Pavlo, Andrew. "Interactive, tree-based graph visualization /." Link to online version, 2006. https://ritdml.rit.edu/dspace/handle/1850/1543.

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Tu, Ying. "Focus-based Interactive Visualization for Structured Data." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366198735.

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Kister, Ulrike. "Interactive Visualization Lenses:." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-236782.

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Information visualization is an important research field concerned with making sense and inferring knowledge from data collections. Graph visualizations are specific techniques for data representation relevant in diverse application domains among them biology, software-engineering, and business finance. These data visualizations benefit from the display space provided by novel interactive large display environments. However, these environments also cause new challenges and result in new requirements regarding the need for interaction beyond the desktop and according redesign of analysis tools. This thesis focuses on interactive magic lenses, specialized locally applied tools that temporarily manipulate the visualization. These may include magnification of focus regions but also more graph-specific functions such as pulling in neighboring nodes or locally reducing edge clutter. Up to now, these lenses have mostly been used as single-user, single-purpose tools operated by mouse and keyboard. This dissertation presents the extension of magic lenses both in terms of function as well as interaction for large vertical displays. In particular, this thesis contributes several natural interaction designs with magic lenses for the exploration of graph data in node-link visualizations using diverse interaction modalities. This development incorporates flexible switches between lens functions, adjustment of individual lens properties and function parameters, as well as the combination of lenses. It proposes interaction techniques for fluent multi-touch manipulation of lenses, controlling lenses using mobile devices in front of large displays, and a novel concept of body-controlled magic lenses. Functional extensions in addition to these interaction techniques convert the lenses to user-configurable, personal territories with use of alternative interaction styles. To create the foundation for this extension, the dissertation incorporates a comprehensive design space of magic lenses, their function, parameters, and interactions. Additionally, it provides a discussion on increased embodiment in tool and controller design, contributing insights into user position and movement in front of large vertical displays as a result of empirical investigations and evaluations
Informationsvisualisierung ist ein wichtiges Forschungsfeld, das das Analysieren von Daten unterstützt. Graph-Visualisierungen sind dabei eine spezielle Variante der Datenrepräsentation, deren Nutzen in vielerlei Anwendungsfällen zum Einsatz kommt, u.a. in der Biologie, Softwareentwicklung und Finanzwirtschaft. Diese Datendarstellungen profitieren besonders von großen Displays in neuen Displayumgebungen. Jedoch bringen diese Umgebungen auch neue Herausforderungen mit sich und stellen Anforderungen an Nutzerschnittstellen jenseits der traditionellen Ansätze, die dadurch auch Anpassungen von Analysewerkzeugen erfordern. Diese Dissertation befasst sich mit interaktiven „Magischen Linsen“, spezielle lokal-angewandte Werkzeuge, die temporär die Visualisierung zur Analyse manipulieren. Dabei existieren zum Beispiel Vergrößerungslinsen, aber auch Graph-spezifische Manipulationen, wie das Anziehen von Nachbarknoten oder das Reduzieren von Kantenüberlappungen im lokalen Bereich. Bisher wurden diese Linsen vor allem als Werkzeug für einzelne Nutzer mit sehr spezialisiertem Effekt eingesetzt und per Maus und Tastatur bedient. Die vorliegende Doktorarbeit präsentiert die Erweiterung dieser magischen Linsen, sowohl in Bezug auf die Funktionalität als auch für die Interaktion an großen, vertikalen Displays. Insbesondere trägt diese Dissertation dazu bei, die Exploration von Graphen mit magischen Linsen durch natürliche Interaktion mit unterschiedlichen Modalitäten zu unterstützen. Dabei werden flexible Änderungen der Linsenfunktion, Anpassungen von individuellen Linseneigenschaften und Funktionsparametern, sowie die Kombination unterschiedlicher Linsen ermöglicht. Es werden Interaktionstechniken für die natürliche Manipulation der Linsen durch Multitouch-Interaktion, sowie das Kontrollieren von Linsen durch Mobilgeräte vor einer Displaywand vorgestellt. Außerdem wurde ein neuartiges Konzept körpergesteuerter magischer Linsen entwickelt. Funktionale Erweiterungen in Kombination mit diesen Interaktionskonzepten machen die Linse zu einem vom Nutzer einstellbaren, persönlichen Arbeitsbereich, der zudem alternative Interaktionsstile erlaubt. Als Grundlage für diese Erweiterungen stellt die Dissertation eine umfangreiche analytische Kategorisierung bisheriger Forschungsarbeiten zu magischen Linsen vor, in der Funktionen, Parameter und Interaktion mit Linsen eingeordnet werden. Zusätzlich macht die Arbeit Vor- und Nachteile körpernaher Interaktion für Werkzeuge bzw. ihre Steuerung zum Thema und diskutiert dabei Nutzerposition und -bewegung an großen Displaywänden belegt durch empirische Nutzerstudien

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Wictorin, Sebastian. "Streamlining Data Journalism: Interactive Analysis in a Graph Visualization Environment." Thesis, Malmö universitet, Fakulteten för kultur och samhälle (KS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-22498.

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This thesis explores the topic of how one can streamline a data journalists analytical workflow in a graph visualization environment. Interactive graph visualizations have been used recently by data journalists to investigate the biggest leaks of data in history. Graph visualizations empower users to find patterns in their connected data, and as the world continuously produces more data, the more important it becomes to make sense of it. The exploration was done by conducting semi-structured interviews with users, which illuminated three categories of insights called Graph Readability, Charts in Graphs and Temporality. Graph Readability was the category that were conceptualized and designed by integrating user research and data visualization best practises. The design process was concluded with a usability test with graph visualization developers, followed by a final iteration of the concept. The outcome resulted in a module that lets users simplify their graph and preserve information by aggregating nodes with similar attributes.

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Kister, Ulrike [Verfasser], Raimund [Akademischer Betreuer] Dachselt, Raimund [Gutachter] Dachselt, and Petra [Gutachter] Isenberg. "Interactive Visualization Lenses: : Natural Magic Lens Interaction for Graph Visualization / Ulrike Kister ; Gutachter: Raimund Dachselt, Petra Isenberg ; Betreuer: Raimund Dachselt." Dresden : Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://d-nb.info/1161669582/34.

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Faronius, Hofmann Therese, and Linda Håkansson. "Visualization Design Effects on Credibility and Data Perception, and the Importance of Digital Interaction." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-453694.

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An effective visualization can often give an insight into data that would otherwise be difficult to analyze. The company Assedon aims to make data understandable to their clients by using data visualization in an interactive user interface. The goal of this study was to create an interactive visual representation of data from the Swedish Public Employment Service with the use of dynamically created digital graphs that are considered credible and beneficial for data perception. Moreover, the goal was to study data perception of the digitally displayed and interactive graphs. The study was conducted by interviewing 19 people with different backgrounds, using a combination of a qualitative and a quantitative interview technique. The interviewees were shown three different designs of a graph type, and rated the graph as well as commented on the graph. The results of this study indicated that a graph is more likely to be perceived as credible if it looks modern and professional. This also means that the design of the graphs needs more attention than people might normally appreciate. The perception of data presented in digitally displayed graphs will be affected by several factors, but most prominently the choice of color can either enhance the perception or confuse. Lastly, interaction with the data will benefit the perception and create another dimension of the data, but only to a certain extent. If the graph is too difficult to evaluate, the purpose of the graph is lost and the interaction becomes a necessity instead of an asset.
En graf kan ge insikt i data som annars är svår att analysera. It-företaget Assedons mål är att konvertera data till digitala interaktiva lösningar som gör data förståelig för deras klienter. Målet med denna studie var att skapa en interaktiv visuell representation av Arbetsförmedlingens data i ett användarvänligt gränssnitt. Detta gjordes genom att skapa digitala grafer som anses trovärdiga och fördelaktiga för datauppfattningen. Målet var även att undersöka hur datauppfattningen av digitala grafer påverkades av interaktion med dessa grafer. Studien utfördes genom att intervjua 19 personer från olika bakgrunder med användning av kvalitativa och kvantitativa intervjutekniker. Deltagarna i studien visades tre olika interaktiva designer av en graf typ och betygsatte dessa samt kommenterade. Resultaten visade att en digital graf är mer sannolik att uppfattas som trovärdig om den ser modern och professionell ut. Datauppfattningen påverkades av flera faktorer, främst färgvalen som kan förtydliga data, men även förvirra läsaren. Avslutningsvis, så kan interaktion erbjuda en ytterligare dimension till grafer och därmed förbättra förståelsen av data. Dock till en viss gräns, är grafen för svår att evaluera utan tillgång till interaktionen så förloras syftet med grafen och interaktionen blir en nödvändighet istället för en tillgång.

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Eriksson, Anton. "Interactive visualization of community structure in complex networks." Thesis, Umeå universitet, Institutionen för fysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-148551.

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Several applied sciences model system dynamics with networks. Since networks often contain thousands or millions of nodes and links, researchers have developed methods that reveal and high- light their essential structures. One such method developed by researchers in IceLab uses information theory to compress descrip- tions of network flows with memory based on paths rather than links and identify hierarchically nested modules with long flow persistence times. However, current visualization tools for navigat- ing and exploring nested modules build on obsolete software that requires plugins and cannot handle such memory networks. Drawing from ideas in cartography, this thesis presents a pow- erful visualization method that enables researchers to analyze and explore modular decompositions of any network. The resulting application uses an efficient graph layout algorithm adapted with a simulation based on information flow. Like in a topographic map, zooming into the map successively reveals more detailed commu- nity structures and network features in a continuous fashion.

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Beutel, Thomas E. "Development and Evaluation of Interactive Courseware for Visualization of Graph Data Structure and Algorithms." NSUWorks, 1997. http://nsuworks.nova.edu/gscis_etd/410.

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The primary goal of this dissertation was to develop and pilot test interactive, multimedia courseware which would facilitate learning the abstract structures, operations, and concepts associated with graph and network data structures in Computer Science. Learning objectives and prerequisites are presented in an introduction section of the courseware and a variety of learning activities are provided including tutorials, animated demonstrations, interactive laboratory sessions, and self-tests. Courseware development incorporated principles and practices from software engineering, instructional design, and cognitive learning theories. Implementation utilized an easy-to-use authoring tool, NeoBook Professional (1994), to create the overall framework and the user interfaces, and Microsoft QuickBASIC 4.5 (1990) to program the interactive animated demonstrations and laboratory exercises. A major emphasis of the courseware is the use of simple interactive, animated displays to demonstrate the step-by-step operation of graph and network algorithms such as depth-first traversal, breadth-first traversal, shortest path, minimum sparring tree and topological ordering.

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Spritzer, Andre Suslik. "Supporting the design of custom static node-ling graph visualization." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2015. http://hdl.handle.net/10183/122650.

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Visualizações de grafos para comunicação aparecem numa variedade de contextos que vão do acadêmico-científico até o jornalístico e até mesmo artístico. Diferente de visualizações de grafos para exploração e análise de dados, essas imagens são usadas para “contar uma história” que já se conhece ao invés da “procura de uma nova história” nos dados. Apesar de ser possível usar software para desenho de grafos e edição de diagramas para produzí-las, visualizações feitas dessa forma nem sempre preenchem os requisitos visuais impostos pelos seus contextos de uso. Programas de edição de imagens podem ser usados para fazer as melhorias necessárias, mas nem todas as modificações são possíveis e o processo de editar essas imagens pode exigir muito tempo e esforço. Neste trabalho, apresentamos uma investigação de visualizações nodo-aresta estáticas para comunicação e de como facilitar sua criação. A partir de uma desconstrução dessas imagens, identificando seus elementos essenciais, e analisando como são criadas, derivamos um conjunto de requisitos que ferramentas para a criação dessas visualizações devem preencher. Para verificar o efeito da metodologia na melhora do fluxo de trabalho de designers, com mais poder e flexibilidade, foi concebido e implementado um protótipo chamado GraphCoiffure. Com um foco especial em auxiliar usuários na criação de visualizações para publicação, Graph- Coiffure foi projetado como uma aplicação standalone que seria usada como um passo intermediário entre programas de desenho e edição de grafos e editores gráficos. Ele combina ferramentas para manipulação interativa de layouts com estilização similar a CSS para permitir que usuários criem e editem visualizações nodo-aresta estáticas. Ilustramos o funcionamento de GraphCoiffure com quatro casos de uso: a adaptação do layout de uma visualização para fazê-la funcionar em uma dada página, a reprodução do estilo de uma visualização e sua aplicação em outro grafo, e a criação integral de duas novas visualizações. Para obter feedback sobre GraphCoiffure, conduzimos uma avaliação informal através de entrevistas com três potenciais usuários, que disseram achar que GraphCoiffure beneficiaria seu trabalho.
Graph visualizations for communication appear in a variety of contexts that range from scientific/ academic to journalistic and even artistic. Unlike graph visualizations for exploration and analysis, these images are used to tell a story that is already known rather than to look for a story within the data. Although graph drawing and diagram editing software can be used to produce them, visualizations made this way do not always meet the visual requirements imposed by their context of use. Graphics authoring software can be used to make the necessary improvements, but not all modifications are possible and the process of editing these images may be very time-consuming and labor-intensive. In this work, we present an investigation of static node-link visualizations for communication and how to better support their creation. We began with a deconstruction of these images, breaking them down into their basic elements and analyzing how they are created. From this, we derived a set of requirements that tools aimed at supporting their creation should meet. To verify if taking all of this into account would improve the workflow and bring more flexibility and power to the users, we created our own prototype, which we named GraphCoiffure. With a special emphasis on helping users on creating visualizations for publication, GraphCoiffure was designed as a standalone application that would serve as an intermediary step between graph drawing and editing software and graphics editors. It combines interactive graph layout manipulation tools with CSS-like styling possibilities to let users create and edit static node-link visualizations for communication. We illustrate the use of GraphCoiffure with four use-case scenarios: the adaptation of a visualization’s layout to make it work on a given page, the reproduction of a visualization’s style and its application on another graph, and the creation of two visualizations from scratch. To obtain feedback on GraphCoiffure, we conducted an informal evaluation by interviewing three potential expert users, who found that it could be useful for their work.

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Voroshilova, Alexandra. "Comparison study on graph sampling algorithms for interactive visualizations of large-scale networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254656.

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Networks are present in computer science, sociology, biology, and neuroscience as well as in applied fields such as transportation, communication, medical industries. The growing volumes of data collection are pushing scalability and performance requirements on graph algorithms, and at the same time, a need for a deeper understanding of these structures through visualization arises. Network diagrams or graph drawings can facilitate the understanding of data, making intuitive the identification of the largest clusters, the number of connected components, the overall structure, and detecting anomalies, which is not achievable through textual or matrix representations. The aim of this study was to evaluate approaches that would enable visualization of a large scale peer-to-peer video live streaming networks. The visualization of such large scale graphs has technical limitations which can be overcome by filtering important structural data from the networks. In this study, four sampling algorithms for graph reduction were applied to large overlay peer-to-peer network graphs and compared. The four algorithms cover different approaches: selecting links with the highest weight, selecting nodes with the highest cumulative weight, using betweenness centrality metrics, and constructing a focus-based tree. Through the evaluation process, it was discovered that the algorithm based on betweenness centrality approximation offers the best results. Finally, for each of the algorithms in comparison, their resulting sampled graphs were visualized using a forcedirected layout with a 2-step loading approach to depict their effect on the representation of the graphs.
Nätverk återfinns inom datavetenskap, sociologi, biologi och neurovetenskap samt inom tillämpade områden så som transport, kommunikation och inom medicinindustrin. Den växande mängden datainsamling pressar skalbarheten och prestandakraven på grafalgoritmer, samtidigt som det uppstår ett behov av en djupare förståelse av dessa strukturer genom visualisering. Nätverksdiagram eller grafritningar kan underlätta förståelsen av data, identifiera de största grupperna, ett antal anslutna komponenter, visa en övergripande struktur och upptäcka avvikelser, något som inte kan uppnås med texteller matrisrepresentationer. Syftet med denna studie var att utvärdera tillvägagångssätt som kunde möjliggöra visualisering av ett omfattande P2P (peer-to-peer) livestreamingnätverk. Visualiseringen av större grafer har tekniska begränsningar, något som kan lösas genom att samla viktiga strukturella data från nätverken. I den här studien applicerades fyra provtagningsalgoritmer för grafreduktion på stora överlagringar av P2P-nätverksgrafer för att sedan jämföras. De fyra algoritmerna är baserade på val av länkar med högsta vikt, av nodar med högsta kumulativa vikt, betweenness-centralitetsvärden för att konstruera ett fokusbaserat träd som har de längsta vägarna uteslutna. Under utvärderingsprocessen upptäcktes det att algoritmen baserad på betweenness-centralitetstillnärmning visade de bästa resultaten. Dessutom, för varje algoritm i jämförelsen, visualiserades deras slutliga samplade grafer genom att använda en kraftstyrd layout med ett 2-stegs laddningsinfart.

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Gobel, Balazs. "AniMap: An Interactive Visualization Supporting Serendipitous Discovery of Information about Anime." Thesis, Malmö högskola, Fakulteten för kultur och samhälle (KS), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-23608.

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It is a challenging task for interaction designers to find a way to design a digital artefact supporting serendipitous discovery. Its interdisciplinary nature requires sufficient knowledge of information visualization, social navigation and serendipity. Based on literature review and prior relevant works, several traces having potential to aid such exploration were defined. Through creating and testing AniMap, an interactive graph visualization for discovering new anime clips, in this thesis I argue that such an artefact has the potential to support serendipitous discovery, owing to its features of being information visualization, interactive and in a graph layout, coupled with users’ personal interests. Even so, finding details of how to influence serendipitous discovery remain an ongoing challenge considering the dynamic nature of serendipity.

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Ren, Haolin. "Visualizing media with interactive multiplex networks." Thesis, Bordeaux, 2019. http://www.theses.fr/2019BORD0036/document.

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Les flux d’information suivent aujourd’hui des chemins complexes: la propagation des informations, impliquant éditeurs on-line, chaînes d’information en continu et réseaux sociaux, emprunte alors des chemins croisés, susceptibles d’agir sur le contenu et sa perception. Ce projet de thèse étudie l’adaptation des mesures de graphes classiques aux graphes multiplexes en relation avec le domaine étudié, propose de construire des visualisations à partir de plusieurs représentations graphiques des réseaux, et de les combiner (visualisations multi-vues synchronisées, représentations hybrides, etc.). L’accent est mis sur les modes d’interaction permettant de prendre en compte l’aspect multiplexe (multicouche) des réseaux. Ces représentations et manipulations interactives s’appuient aussi sur le calcul d’indicateurs propres aux réseaux multiplexes. Ce travail est basé sur deux jeux de données principaux: l’un est une archive de 12 ans de l’émission japonaise publique quotidienne NHK News 7, de 2001 à 2013. L’autre recense les participants aux émissions de télévision/radio françaises entre 2010 et 2015. Deux systèmes de visualisation s’appuyant sur une interface Web ont été développés pour analyser des réseaux multiplexes, que nous appelons «Visual Cloud» et «Laputa». Dans le Visual Cloud, nous définissons formellement une notion de similitude entre les concepts et les groupes de concepts que nous nommons possibilité de co-occurrence (CP). Conformément à cette définition, nous proposons un algorithme de classification hiérarchique. Nous regroupons les couches dans le réseau multiplexe de documents, et intégrons cette hiérarchie dans un nuage de mots interactif. Nous améliorons les algorithmes traditionnels de disposition de mise en forme de nuages de mots de sorte à préserver les contraintes sur la hiérarchie de concepts. Le système Laputa est destiné à l’analyse complexe de réseaux temporels denses et multidimensionnels. Pour ce faire, il associe un graphe à une segmentation. La segmentation par communauté, par attribut, ou encore par tranche temporelle, forme des vues de ce graphe. Afin d’associer ces vues avec le tout global, nous utilisons des diagrammes de Sankey pour révéler l’évolution des communautés (diagrammes que nous avons augmentés avec un zoom sémantique). Cette thèse nous permet ainsi de parcourir trois aspects (3V) des plus intéressants de la donnée et du BigData appliqués aux archives multimédia: Le Volume de nos données dans l’immensité des archives, nous atteignons des ordres de grandeurs qui ne sont pas praticables pour la visualisation et l’exploitation des liens. La Vélocité à cause de la nature temporelle de nos données (par définition). La Variété qui est un corollaire de la richesse des données multimédia et de tout ce que l’on peut souhaiter vouloir y investiguer. Ce que l’on peut retenir de cette thèse c’est que la traduction de ces trois défis a pris dans tous les cas une réponse sous la forme d’une analyse de réseaux multiplexes. Nous retrouvons toujours ces structures au coeur de notre travail, que ce soit de manière plus discrète dans les critères pour filtrer les arêtes par l’algorithme Simmelian backbone, que ce soit par la superposition de tranches temporelles, ou bien que ce soit beaucoup plus directement dans la combinaison d’indices sémantiques visuels et textuels pour laquelle nous extrayons les hiérarchies permettant notre visualisation
Nowadays, information follows complex paths: information propagation involving on-line editors, 24-hour news providers and social medias following entangled paths acting on information content and perception. This thesis studies the adaptation of classical graph measurements to multiplex graphs, to build visualizations from several graphical representations of the networks, and to combine them (synchronized multi-view visualizations, hybrid representations, etc.). Emphasis is placed on the modes of interaction allowing to take in hand the multiplex nature (multilayer) of the networks. These representations and interactive manipulations are also based on the calculation of indicators specific to multiplex networks. The work is based on two main datasets: one is a 12-year archive of the Japanese public daily broadcast NHK News 7, from 2001 to 2013. Another lists the participants in the French TV/radio shows between 2010 and 2015. Two visualization systems based on a Web interface have been developed for multiplex network analysis, which we call "Visual Cloud" and "Laputa". In the Visual Cloud, we formally define a notion of similarity between concepts and groups of concepts that we call co-occurrence possibility (CP). According to this definition, we propose a hierarchical classification algorithm. We aggregate the layers in a multiplex network of documents, and integrate that hierarchy into an interactive word cloud. Here we improve the traditional word cloud layout algorithms so as to preserve the constraints on the concept hierarchy. The Laputa system is intended for the complex analysis of dense and multidimensional temporal networks. To do this, it associates a graph with a segmentation. The segmentation by communities, by attributes, or by time slices, forms views of this graph. In order to associate these views with the global whole, we use Sankey diagrams to reveal the evolution of the communities (diagrams that we have increased with a semantic zoom). This thesis allows us to browse three aspects of the most interesting aspects of the data miming and BigData applied to multimedia archives: The Volume since our archives are immense and reach orders of magnitude that are usually not practicable for the visualization; Velocity, because of the temporal nature of our data (by definition). The Variety that is a corollary of the richness of multimedia data and of all that one may wish to want to investigate. What we can retain from this thesis is that we met each of these three challenges by taking an answer in the form of a multiplex network analysis. These structures are always at the heart of our work, whether in the criteria for filtering edges using the Simmelian backbone algorithm, or in the superposition of time slices in the complex networks, or much more directly in the combinations of visual and textual semantic indices for which we extract hierarchies allowing our visualization

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Armstrong, Christopher J. "Live Surface." BYU ScholarsArchive, 2007. https://scholarsarchive.byu.edu/etd/1029.

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Live Surface allows users to segment and render complex surfaces from 3D image volumes at interactive (sub-second) rates using a novel, Cascading Graph Cut (CGC). Live Surface consists of two phases. (1) Preprocessing for generation of a complete 3D watershed hierarchy followed by tracking of all catchment basin surfaces. (2) User interaction in which, with each mouse movement, the 3D object is selected and rendered in real time. Real-time segmentation is ccomplished by cascading through the 3D watershed hierarchy from the top, applying graph cut successively at each level only to catchment basins bordering the segmented surface from the previous level. CGC allows the entire image volume to be segmented an order of magnitude faster than existing techniques that make use of graph cut. OpenGL rendering provides for display and update of the segmented surface at interactive rates. The user selects objects by tagging voxels with either (object) foreground or background seeds. Seeds can be placed on image cross-sections or directly on the 3D rendered surface. Interaction with the rendered surface improves the user's ability to steer the segmentation, augmenting or subtracting from the current selection. Segmentation and rendering, combined, is accomplished in about 0.5 seconds, allowing 3D surfaces to be displayed and updated dynamically as each additional seed is deposited. The immediate feedback of Live Surface allows for the segmentation of 3D image volumes with an interaction paradigm similar to the Live Wire (Intelligent Scissors) tool used in 2D images.

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Lambert, Antoine. "Visualisation interactive de graphes : élaboration et optimisation d'algorithmes à coûts computationnels élevés." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2012. http://tel.archives-ouvertes.fr/tel-00839243.

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Un graphe est un objet mathématique modélisant des relations sur un ensemble d' éléments. Il est utilisé dans de nombreux domaines a des fi ns de modélisation. La taille et la complexité des graphes manipulés de nos jours entraînent des besoins de visualisation a fin de mieux les analyser. Dans cette thèse, nous présentons différents travaux en visualisation interactive de graphes qui s'attachent a exploiter les architectures de calcul parallèle (CPU et GPU) disponibles sur les stations de travail contemporaines. Un premier ensemble de travaux s'intéresse a des problématiques de dessin de graphes. Dessiner un graphe consiste a le plonger visuellement dans un plan ou un espace. La première contribution dans cette thématique est un algorithme de regroupement d'arêtes en faisceaux appelé Winding Roads. Cet algorithme intuitif, facilement implémentable et parallélisable permet de reduire considérablement les problèmes d'occlusion dans un dessin de graphe dus aux nombreux croisements d'arêtes. La seconde contribution est une méthode permettant de dessiner un réseau métabolique complet. Ce type de reseau modélise l'ensemble des réactions biochimiques se produisant dans les cellules d'un organisme vivant. L'avantage de la méthode est de prendre en compte la décomposition du réseau en sous-ensembles fonctionnels ainsi que de respecter les conventions de dessin biologique. Un second ensemble de travaux porte sur des techniques d'infographie pour la visualisation interactive de graphes. La première contribution dans cette thématique est une technique de rendu de courbes paramétriques exploitant pleinement le processeur graphique. La seconde contribution est une méthode de rendu nommée Edge splatting permettant de visualiser la densité des faisceaux d'arêtes dans un dessin de graphe avec regroupement d'arêtes. La dernière contribution porte sur des techniques permettant de mettre en évidence des sous-graphes d'interêt dans le contexte global d'une visualisation de graphes.

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Ekhtiari, Amiri Sorour. "Task-specific summarization of networks: Optimization and Learning." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/100993.

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Networks (also known as graphs) are everywhere. People-contact networks, social networks, email communication networks, internet networks (among others) are examples of graphs in our daily life. The increasing size of these networks makes it harder to understand them. Instead, summarizing these graphs can reveal key patterns and also help in sensemaking as well as accelerating existing graph algorithms. Intuitively, different summarizes are desired for different purposes. For example, to stop viral infections, one may want to find an effective policy to immunize people in a people-contact network. In this case, a high-quality network summary should highlight roughly structurally important nodes. Others may want to detect communities in the same people-contact network, and hence, the summary should show cohesive groups of nodes. This implies that for each task, we should design a specific method to reveal related patterns. Despite the importance of task-specific summarization, there has not been much work in this area. Hence, in this thesis, we design task-specific summarization frameworks for univariate and multivariate networks. We start with optimization-based approaches to summarize graphs for a particular task and finally propose general frameworks which automatically learn how to summarize for a given task and generalize it to similar networks. 1. Optimization-based approaches: Given a large network and a task, we propose summarization algorithms to highlight specific characteristics of the graph (i.e., structure, attributes, labels, dynamics) with respect to the task. We develop effective and efficient algorithms for various tasks such as content-aware influence maximization and time segmentation. In addition, we study many real-world networks and their summary graphs such as people-contact, news-blogs, etc. and visualize them to make sense of their characteristics given the input task. 2. Learning-based approaches: As our next step, we propose a unified framework which learns the process of summarization itself for a given task. First, we design a generalizable algorithm to learn to summarize graphs for a set of graph optimization problems. Next, we go further and add sparse human feedback to the learning process for the given optimization task. To the best of our knowledge, we are the first to systematically bring the necessity of considering the given task to the forefront and emphasize the importance of learning-based approaches in network summarization. Our models and frameworks lead to meaningful discoveries. We also solve problems from various domains such as epidemiology, marketing, social media, cybersecurity, and interactive visualization.
Doctor of Philosophy

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Lee, Bongshin. "Interactive visualizations for trees and graphs." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3519.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.
Thesis research directed by: Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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ZHONG, LI. "SHORTCUT BASED GRAPH COARSENING FOR PROTEIN INTERACTION NETWORK VISUALIZATION." University of Cincinnati / OhioLINK, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=ucin997457452.

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Spritzer, Andre Suslik. "MagnetViz : design and evaluation of a physics-based interaction technique for graph visualization." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2009. http://hdl.handle.net/10183/17023.

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Esta dissertação apresenta MagnetViz, uma técnica para visualização de grafos. Enquanto a maior parte das técnicas visualizam um layout de grafo estático pre-computado, MagnetViz permite que usuários dinamicamente alterem o layout de um grafo de forma a melhor satisfazer suas necessidades. Isso é feito ao construir em cima da metáfora de física de algoritmos dirigidos à força para proporcionar aos usuários imãs virtuais, que podem atrair nodos que satisfazem um conjunto de critérios associados a eles. Critérios podem ser baseados na topologia ou semântica do grafo. Através de boundary shapes, que são simples formas geométricas que podem ser colocadas ao redor de imãs, usuários podem também definir regiões na cena onde os nodos atraídos devem permanecer. Grafos são descritos usando GraphML, uma linguagem baseada em XML, que permite a especificação dos nodos e arestas e de atributos para essas entidades. Após a submissão de um grafo como entrada, MagnetViz o exibe utilizando uma versão modificada do algoritmo clássico de Fruchterman and Rheingold, e permite que usuário, a seguir, insira imãs na cena. Usuários podem construir as condições associadas aos imãs utilizando os atributos dos nodos e arestas, além de atributos topológicos próprios de grafos. Para a avaliação de MagnetViz, foi primeiro analisado o desempenho da técnica ao ajudar usuários a executarem tarefas definidas por uma taxonomia de tarefas de visualização de grafos encontrada na literatura. Então, MagnetViz foi testada em um contexto prático através de um estudo de caso. Uma rede de co-autorias foi escolhida como conjunto de dados e o protótipo de MagnetViz foi inicialmente usado para responder questões relevantes a esses dados e então testado por um grupo de potenciais usuários, que tinham de usa-lo para responder essas mesmas perguntas. Após testar a aplicação, os sujeiotos receberam questionários sobre usas opiniões quanto a usabilidade, aplicabilidade, relevância e resultados visuais da técnica. Enquanto alguns aspectos da técnica ainda podem ser melhorados, os resultados da avaliação provaram que MagnetViz é uma abordagem válida para interação com visualizações de grafos.
This dissertation presents MagnetViz, a technique for the visualization of graphs. While most techniques visualize a static pre-computed graph layout, MagnetViz allows users to dynamically alter the layout of a graph to better satisfy their needs. This is done by building on the physics metaphor of force-directed algorithms to provide users with virtual magnets, which can attract nodes that fulfill a set of criteria associated with them. Criteria can be based on either the topology or semantics of the graph. Through boundary shapes, which are simple geometric shapes that can be placed around magnets, users can also define regions within the scene where the attracted nodes should remain. Graphs are described in GraphML, a XML-like description language which allows the specification of nodes and edges between nodes as well as attributes associated to nodes and edges. After loading a graph, Magnetviz displays it using a slightly modified version of the classical Fruchterman and Reingold' algorithm, and allows the user to insert magnets. Users can build the criteria associated with the magnets using the attributes of nodes and/or edges, besides the common graphs' topological attributes. For MagnetViz's evaluation, it was first analyzed how the technique fared in aiding users to perform tasks defined by a graph visualization task taxonomy described in the literature. Then, MagnetViz was tested within a practical context by means of a case study. A co-authorship network was chosen as the target dataset. The MagnetViz prototype was initially used to answer questions relevant to this dataset and then tested by a group of potential users, who had to use it to answer these same questions. After trying the application, subjects answered questionnaires about their opinion on the technique's usability, applicability, relevance and visual results. While some aspects of the technique should still be refined, results of the evaluation proved MagnetViz to be a valid approach when it comes to interaction with graph visualizations.

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Afzal, Mansoor. "Graph-Based Visualization of Ontology-Based Competence Profiles for Research Collaboration." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH. Forskningsmiljö Informationsteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-20123.

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Information visualization can be valuable in a wide range of applications, it deals with abstract, non-spatial data and with the representation of data elements in a meaningful form irrespective of the size of the data, because sometimes visualization itself focuses on the certain key aspects of the data in the representation and thus it helps by providing ease for the goal oriented interpretation. Information visualization focuses on providing a spontaneous and deeper level of the understanding of the data. Research collaboration enhances sharing knowledge and also enhances an individual’s talent. New ideas are generated when knowledge is shared and transferred among each other. According to (He et al, 2009) Research collaboration has been considered as a phenomenon of growing importance for the researchers, also it should be encouraged and is considered to be a “good thing” among the researchers. The main purpose of this thesis work is to prepare a model for the competence profile visualization purpose. For this purpose the study of different visualization techniques that exist in the field of information visualization are discussed in this thesis work. The study and discussion about the visualization techniques motivates in selecting appropriate visualization techniques for the visualization of Ontology-based competence profiles for research collaboration purpose. A proof of concept is developed which shows how these visualization techniques are applied to visualize several components of competence profile.

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Aleksakhin, Vladyslav. "Visualization of gene ontology and cluster analysis results." Thesis, Linnéuniversitetet, Institutionen för datavetenskap, fysik och matematik, DFM, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-21248.

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The purpose of the thesis is to develop a new visualization method for Gene Ontologiesand hierarchical clustering. These are both important tools in biology andmedicine to study high-throughput data such as transcriptomics and metabolomicsdata. Enrichment of ontology terms in the data is used to identify statistically overrepresentedontology terms, that give insight into relevant biological processes orfunctional modules. Hierarchical clustering is a standard method to analyze andvisualize data to nd relatively homogeneous clusters of experimental data points.Both methods support the analysis of the same data set, but are usually consideredindependently. However, often a combined view such as: visualizing a large data setin the context of an ontology under consideration of a clustering of the data.The result of the current work is a user-friendly program that combines twodi erent views for analysing Gene Ontology and Cluster simultaneously. To makeexplorations of such a big data possible we developed new visualization approach.

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Sullivan, Paul Andrew. "Graph-Based Data Visualization in Virtual Reality: A Comparison of User Experiences." DigitalCommons@CalPoly, 2016. https://digitalcommons.calpoly.edu/theses/1598.

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Virtual reality is currently in the spotlight, attracting intense scrutiny by the press, technology companies, and consumers. After twenty years of dormancy, the technology has experienced a renaissance following advancements in both hardware and software. Most of these developments, and thus press attention, have been centered on entertainment. However, if the technology is going to continue to grow, it must be useful in a wide variety of situations. This paper explores the effectiveness of visualizing data in virtual reality in comparison to traditional presentations. In this thesis, we present an approach to displaying data in a virtual reality environment. We drew upon various visualization and design principles in two dimensions (2D) and extended and implemented them in three dimensions (3D). Finally, we experimented with animations to highlight how the immersive qualities of virtual reality could help direct the user's attention to important features. To verify our work, we tested users' ability to understand worldwide economic data represented as graphs. We measured the speed and accuracy of each subject's responses as they viewed the economic data in two environments: a virtual reality (VR) environment using the Oculus Rift to look at our 3D animated chart, and a more traditional environment with a series of 2D paper charts. We concluded that for newcomers to VR, 2D charts are faster and more accurate. However, 3D visualizations are more engaging and are superior when searching for certain kinds of information such as the highest and lowest values in a set.

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King, James Lowell. "Gene Ontology-Guided Force-Directed Visualization of Protein Interaction Networks." Diss., NSUWorks, 2019. https://nsuworks.nova.edu/gscis_etd/1066.

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Protein interaction data is being generated at unprecedented rates thanks to advancements made in high throughput techniques such as mass spectrometry and DNA microarrays. Biomedical researchers, operating under budgetary constraints, have found it difficult to scale their efforts to keep up with the ever-increasing amount of available data. They often lack the resources and manpower required to analyze the data using existing methodologies. These research deficiencies impede our ability to understand diseases, delay the advancement of clinical therapeutics, and ultimately costs lives. One of the most commonly used techniques to analyze protein interaction data is the construction and visualization of protein interaction networks. This research investigated the effectiveness and efficiency of novel domain-specific algorithms for visualizing protein interaction networks. The existing domain-agnostic algorithms were compared to the novel algorithms using several performance, aesthetic, and biological relevance metrics. The graph drawing algorithms proposed here introduced novel domain-specific forces to the existing force-directed graph drawing algorithms. The innovations include an attractive force and graph coarsening policy based on semantic similarity, and a novel graph refinement algorithm. These experiments have demonstrated that the novel graph drawing algorithms consistently produce more biologically meaningful layouts than the existing methods. Aggregated over the 480 tests performed, and quantified using the Biological Evaluation Percentage metric defined in the Methodology chapter, the novel graph drawing algorithms created layouts that are 237 percent more biologically meaningful than the next best algorithm. This improvement came at the cost of additional edge crossings and smaller minimum angles between adjacent edges, both of which are undesirable aesthetics. The aesthetic and performance tradeoffs are experimentally quantified in this study, and dozens of algorithmically generated graph drawings are presented to visually illustrate the benefits of the novel algorithms. The graph drawing algorithms proposed in this study will help biomedical researchers to more efficiently produce high quality interactive protein interaction network drawings for improved discovery and communication.

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Bronge, Erica. "Visualization of Feature Dependency Structures : A case study at Scania CV AB." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-205625.

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As many automotive companies have moved towards a higher degree of variability in the product lines they offer their customers, a necessary need has emerged for so called feature dependency structures that are used to describe product feature dependencies and verify order validity. In this study, the possibility of using a node-link graph representation to visualize such a feature dependency structure and the associated affordances and limitations were investigated by the implementation of a case study at the Swedish automotive company Scania CV AB. Qualitative data gathering methods such as contextual inquiry and semi-structured interviews with employees were used to identify key tasks and issues involved in maintenance and analysis of Scania’s in-house feature dependency structure. These findings were used together with user-supported iterative prototyping to create a few visualization prototypes intended to provide support with performance of some of the identified tasks. User evaluation of the prototypes showed that a node-link graph representation was a viable solution to support users with structure maintenance, exhibiting the following affordances: structure exploration, overview and context. Furthermore, the major limitations of the tested representation were found to be lookup of specific information and access to detail. The findings of this study are expected to be of use for other automotive companies that employ a high degree of feature variability in their product lines through the use of complex feature dependency structures.
I samband med att flera fordonstillverkare gått över till att erbjuda en allt större grad av varians i de produktlinjer man erbjuder sina kunder så har ett nödvändigt behov uppstått av att ha regelverk som beskriver de beroenden som finns mellan produktegenskaper och verifierar att inkomna ordrar är giltiga. I den här studien så har möjligheten att visualisera den typen av regelverk med en så kallad ”node-link”-graf samt de styrkor och svagheter som följer med en sådan representation undersökts genom en fallstudie på den svenska fordonstillverkaren Scania CV AB. Med hjälp av kvalitativa datainsamlingsmetoder som så kallad ”Contextual inquiry” och semistrukturerade intervjuer med anställda specialiserade på underhåll av Scanias egna egenskapsregelverk så kunde nyckeluppgifter och svårigheter relaterade till regelverket identifieras. Dessa upptäckter användes sedan tillsammans med användarcentrerat iterativt prototypande för att skapa ett antal visualiseringsprototyper avsedda att underlätta utförandet av några av de tidigare identifierade uppgifterna. Användarutvärdering av prototyperna visade att en visualisering baserad på en ”node-link”-representation var en gångbar lösning som kunde underlätta för användarna. Dess styrkor var att stödja utforskande av strukturen med bra överblick av innehållet och bibehållet sammanhang. Representation var dock svag när det gällde att stödja användaren i att leta upp specifik information och att tillhandahålla mer ingående detaljer. Dessa resultat förväntas vara användbara för andra fordonstillverkare som bygger sina produktlinjer på en hög grad av varians med hjälp av komplexa beroenderegelverk för produktegenskaper.

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García, Sara. "Visualization of Learning Paths as Networks of Topics." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-100683.

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Nowadays, interactive visualizations have been one of the most used tools in Big Data fields for the purpose of searching for relationships and structured information in large datasets of unstructured information. In this project, these tools are applied to extract structured information from students following Self-Regulated Learning (SRL). By means of an interactive graph, we are able to study the paths that the students follow in the learning materials. Our visualization supports the investigation of patterns of behaviour of the students, which later could be used, for example, to adapt the study program to the student’s needs in a dynamic way or offer guidance if necessary.

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Royer, Loic. "Unraveling the Structure and Assessing the Quality of Protein Interaction Networks with Power Graph Analysis." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-62562.

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Molecular biology has entered an era of systematic and automated experimentation. High-throughput techniques have moved biology from small-scale experiments focused on specific genes and proteins to genome and proteome-wide screens. One result of this endeavor is the compilation of complex networks of interacting proteins. Molecular biologists hope to understand life's complex molecular machines by studying these networks. This thesis addresses tree open problems centered upon their analysis and quality assessment. First, we introduce power graph analysis as a novel approach to the representation and visualization of biological networks. Power graphs are a graph theoretic approach to lossless and compact representation of complex networks. It groups edges into cliques and bicliques, and nodes into a neighborhood hierarchy. We demonstrate power graph analysis on five examples, and show its advantages over traditional network representations. Moreover, we evaluate the algorithm performance on a benchmark, test the robustness of the algorithm to noise, and measure its empirical time complexity at O (e1.71)- sub-quadratic in the number of edges e. Second, we tackle the difficult and controversial problem of data quality in protein interaction networks. We propose a novel measure for accuracy and completeness of genome-wide protein interaction networks based on network compressibility. We validate this new measure by i) verifying the detrimental effect of false positives and false negatives, ii) showing that gold standard networks are highly compressible, iii) showing that authors' choice of confidence thresholds is consistent with high network compressibility, iv) presenting evidence that compressibility is correlated with co-expression, co-localization and shared function, v) showing that complete and accurate networks of complex systems in other domains exhibit similar levels of compressibility than current high quality interactomes. Third, we apply power graph analysis to networks derived from text-mining as well to gene expression microarray data. In particular, we present i) the network-based analysis of genome-wide expression profiles of the neuroectodermal conversion of mesenchymal stem cells. ii) the analysis of regulatory modules in a rare mitochondrial cytopathy: emph{Mitochondrial Encephalomyopathy, Lactic acidosis, and Stroke-like episodes} (MELAS), and iii) we investigate the biochemical causes behind the enhanced biocompatibility of tantalum compared with titanium.

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Yasar, Sevgi. "Multi-resolution Visualization Of Large Scale Protein Networks Enriched With Gene Ontology Annotations." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12611132/index.pdf.

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Genome scale protein-protein interactions (PPIs) are interpreted as networks or graphs with thousands of nodes from the perspective of computer science. PPI networks represent various types of possible interactions among proteins or genes of a genome. PPI data is vital in protein function prediction since functions of the cells are performed by groups of proteins interacting with each other and main complexes of the cell are made of proteins interacting with each other. Recent increase in protein interaction prediction techniques have made great amount of protein-protein interaction data available for genomes. As a consequence, a systematic visualization and analysis technique has become crucial. To the best of our knowledge, no PPI visualization tool consider multi-resolution viewing of PPI network. In this thesis, we implemented a new approach for PPI network visualization which supports multi-resolution viewing of compound graphs. We construct compound nodes and label them by using gene set enrichment methods based on Gene Ontology annotations. This thesis further suggests new methods for PPI network visualization.

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Maushagen, Jan. "Visual Analysis of Publication Networks." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-27487.

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This thesis documents the development of a web-application attacking the problem of visualization of co-authorship networks. The visualization encompasses several views.Each of them shows different aspects of the data which is loaded from Academic Archive Online (DiVa), a library system which holds all publications released in the Linnaeus University. To detect relationships among authors, a new interactive layout for Node-Link Diagrams was developed which shows publications, authors and corresponding organizations (faculties, departments) in a radial manner. This Network-View is connected to another view showing the attributes (year, type) of the publications. In development, particular emphasis was placed on a rich support of user interaction in order to equip the user with a tool that allows graphical and explorative analysis of the underlying data.

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Nur, Kazım Gökberk. "Visualizing Logical Architecture of Electrical and Electronic (E/E) Systems in Automotive Industry." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH, Datateknik och informatik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-47395.

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Modern vehicles equipped with many hardware and software systems. To develop new functionalities and maintain existing features of the vehicles, engineers have to check relationship between software and hardware systems. Due to complexity of these relationships, visual representation of how systems are working together is required to make R&D process easier. At Scania, engineers using node-link diagrams to represent logical function architecture of the Scania vehicles. Logical function architecture is a part of electrical and electronic systems in the automotive industry, due to size of these systems they are considered as a large network. Visualizing large networks by diagrams is not a new problem in literature. At past, researches published about diagram drawing and algorithms have been developed to generate good looking diagram. However, sometimes due to complexity of the data, having complex and unreadable diagrams are unavoidable and they are hard to understand. Previous studies investigated how diagrams should be drawn, however focus was not how users should interact with the diagrams. In node-link diagrams users follows edges to understand relationships between components. Having edges in the diagram heavily affects the diagram drawing time and also required space for the diagram. In this paper I developed an artefact which is not using edges to visualize LFA at Scania. Artefact usability has been tested with Scania engineers by giving some tasks to them. In the tests, artefact without edges achieved better results than node-link diagram and 426% improvement achieved by comparing task completion times in seconds. The artefact proved that it can be powerful alternative to classic node-link diagram visualization.

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Chau, Dueng Horng. "Data Mining Meets HCI: Making Sense of Large Graphs." Research Showcase @ CMU, 2012. http://repository.cmu.edu/dissertations/94.

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We have entered the age of big data. Massive datasets are now common in science, government and enterprises. Yet, making sense of these data remains a fundamental challenge. Where do we start our analysis? Where to go next? How to visualize our findings? We answers these questions by bridging Data Mining and Human- Computer Interaction (HCI) to create tools for making sense of graphs with billions of nodes and edges, focusing on: (1) Attention Routing: we introduce this idea, based on anomaly detection, that automatically draws people’s attention to interesting areas of the graph to start their analyses. We present three examples: Polonium unearths malware from 37 billion machine-file relationships; NetProbe fingers bad guys who commit auction fraud. (2) Mixed-Initiative Sensemaking: we present two examples that combine machine inference and visualization to help users locate next areas of interest: Apolo guides users to explore large graphs by learning from few examples of user interest; Graphite finds interesting subgraphs, based on only fuzzy descriptions drawn graphically. (3) Scaling Up: we show how to enable interactive analytics of large graphs by leveraging Hadoop, staging of operations, and approximate computation. This thesis contributes to data mining, HCI, and importantly their intersection, including: interactive systems and algorithms that scale; theories that unify graph mining approaches; and paradigms that overcome fundamental challenges in visual analytics. Our work is making impact to academia and society: Polonium protects 120 million people worldwide from malware; NetProbe made headlines on CNN, WSJ and USA Today; Pegasus won an opensource software award; Apolo helps DARPA detect insider threats and prevent exfiltration. We hope our Big Data Mantra “Machine for Attention Routing, Human for Interaction” will inspire more innovations at the crossroad of data mining and HCI.

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Bolte, Fabian. "Intuitive Visualisierung universitätsinterner Publikationsdaten zur Unterstützung von Entscheidungsprozessen." Master's thesis, Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-213305.

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Die vorliegende Arbeit nutzt die Publikationsdaten der TU Chemnitz zur Darstellung der Entwicklung von Kooperationen zwischen Instituten und Fakultäten über die Zeit. Dabei wird die Unzulänglichkeit gängiger Netzwerkanalysen mithilfe von Graphen, die komplexen Beziehungen um eine zeitliche Dimension zu erweitern, aufgezeigt. Stattdessen wird eine Anwendung auf Basis des Streamgraphen vorgestellt, welche nicht nur den Vergleich der Entwicklung beliebiger Kombinationen von Instituten und Fakultäten ermöglicht, sondern auch spezifische Auskünfte zu den Kooperationsarten und deren zeitlicher Verlagerung gibt. Dafür werden zwei Erweiterungen für den Streamgraphen vorgestellt, welche seinen Informationsumfang erweitern und ihn damit zur Erfüllung der gesetzten Anforderungen befähigen
This thesis uses data about publications from members of the TU Chemnitz to visualize the progress of cooperations between institutes and faculties over time. Thereby it is shown, that the attempt to expand common used network analyses, via graphs, by a temporal dimension, is insufficient for this task. Instead we present an application, based on a streamgraph, which enables the user to compare the development of any combination of institutes and faculties, as well as giving specific information about cooperation types and their temporal shift. Therefore, two extensions to the streamgraph are proposed, which increase the amount of information visible and provide tools to satisfy the stated requirements

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Heyman, Susanna. "Visualizing Financial Futures." Doctoral thesis, KTH, Medieteknik och interaktionsdesign, MID, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-211657.

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Research on financial decision aids, systems designed to help people make financial decisions, is sparse. Previous research has often focused on the theoretical soundness of the advice that the systems provide.The original contribution of this doctoral thesis is a set of empirical studies of how non-expert people understand the advice provided by financial decision aids. Since every piece of advice must be interpreted by a receiver, the accuracy of the advice can be corrupted along the way if the receiver does not understand complicated terminology, probabilistic reasoning, or abstract concepts.The design concept resulting from the studies visualizes a unique combination of short-term and long-term variables that are usually treated as separate and not interacting with each other; loans and amortizations, insurance, retirement saving, and consumption. The aim is to visualize the consequences of different decisions and possible adverse events in terms of their effect on the user’s future consumption, rather than abstract numbers detached from the user’s lived experience.The design concept was tested and evaluated by personal finance experts and professional financial advisors, as well as students and people without financial education, who represented the target users of the system. Results indicate that the system has a learning curve, but that once users understand how to read the graph, they find it more informative than conventional financial planning tools.

QC 20170809

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Vargas, Gonzalez Andres. "SketChart: A Pen-Based Tool for Chart Generation and Interaction." Master's thesis, University of Central Florida, 2014. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6375.

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It has been shown that representing data with the right visualization increases the understanding of qualitative and quantitative information encoded in documents. However, current tools for generating such visualizations involve the use of traditional WIMP techniques, which perhaps makes free interaction and direct manipulation of the content harder. In this thesis, we present a pen-based prototype for data visualization using 10 different types of bar based charts. The prototype lets users sketch a chart and interact with the information once the drawing is identified. The prototype's user interface consists of an area to sketch and touch based elements that will be displayed depending on the context and nature of the outline. Brainstorming and live presentations can benefit from the prototype due to the ability to visualize and manipulate data in real time. We also perform a short, informal user study to measure effectiveness of the tool while recognizing sketches and users acceptance while interacting with the system. Results show SketChart strengths and weaknesses and areas for improvement.
M.S.
Masters
Electrical Engineering and Computer Science
Engineering and Computer Science
Computer Science

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Bach, Benjamin. "Connections, changes, and cubes : unfolding dynamic networks for visual exploration." Phd thesis, Université Paris Sud - Paris XI, 2014. http://tel.archives-ouvertes.fr/tel-01020535.

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Networks are models that help us understanding and thinking about relationships between entities in the real world. Many of these networks are dynamic, i.e. connectivity changes over time. Understanding changes in connectivity means to understand interactions between elements of complex systems; how people create and break up friendship relations, how signals get passed in the brain, how business collaborations evolve, or how food-webs restructure after environmental changes. However, understanding static networks is already difficult, due to size, density, attributes and particular motifs; changes over time very much increase this complexity. Quantification of change is often insufficient, but beyond an analysis that is driven by technology and algorithms, humans dispose a unique capability of understanding and interpreting information in data, based on vision and cognition. This dissertation explores ways to interactively explore dynamic networks by means of visualization. I develop and evaluate techniques to unfold the complexity of dynamic networks, making them understandable by looking at them from different angles, decomposing them into their parts and relating the parts in novel ways. While most techniques for dynamic network visualization rely on one particular type of view on the data, complementary visualizations allow for higher-level exploration and analysis. Covering three aspects Tasks, Visualization Design and Evaluation, I develop and evaluate the following unfolding techniques: (i) temporal navigation between individual time steps of a network and improved animated transitions to better understand changes, (ii) designs for the comparison of weighted graphs, (iii) the Matrix Cube, a space-time cube based on adjacency matrices, allowing to visualize dense dynamic networks by, as well as GraphCuisine, a system to (iv) generate synthetic networks with the primary focus on evaluating visualizations in user studies. In order to inform the design and evaluation of visualizations, we (v) provide a task taxonomy capturing users' tasks when exploring dynamic networks. Finally, (vi) the idea of unfolding networks with Matrix Cubes is generalized to other data sets that can be represented in space-time cubes (videos, geographical data, etc.). Visualizations in these domains can inspire visualizations for dynamic networks, and vice-versa. We propose a taxonomy of operations, describing how 3D space-time cubes are decomposed into a large variety of 2D visualizations. These operations help us exploring the design space for visualizing and interactively unfolding dynamic networks and other spatio-temporal data, as well as may serve users as a mental model of the data.

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Sallaberry, Arnaud. "Visualisation d'information : de la théorie sémiotique à des exemples pratiques basés sur la représentation de graphes et d'hypergraphes." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2011. http://tel.archives-ouvertes.fr/tel-00646397.

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La visualisation d'information est une discipline récente en pleine expansion et qui a pour objet l'étude des méthodes de représentation visuelle de données abstraites, c'est-à-dire non géolocalisées. La sémiotique est quant à elle une discipline beaucoup plus ancienne (fin du XIXième siècle) qui s'intéresse aux divers systèmes de signes nécessaires aux processus de communication. A ce jour, peu de travaux ont été réalisés pour mettre en parallèle ces deux disciplines. C'est pourquoi le premier chapitre de cette thèse est dédié à l'étude de la visualisation d'information selon les paradigmes élaborés par son ainée tout au long du XXième siècle. Nous montrons en particulier comment l'un des modèles les plus aboutis de validation de visualisations (modèle imbriqué de Tamara Munzner) correspond au processus d'étude sémiotique d'énoncés. Le second chapitre est consacré à la visualisation de graphe, outil de modélisation puissant de divers ensembles de données abstraites. Nous proposons d'une part une application permettant de visualiser et de naviguer à travers les pages Internet retournées par un moteur de recherche et d'autre part un algorithme de visualisation de hiérarchies dynamiques sous forme de "cartes géographiques". Enfin, nous évoquons dans le troisième chapitre un autre outil de modélisation de données abstraites : les hypergraphes. Nous proposons des résultats théoriques concernant leur représentation et donnons une ébauche de solution permettant de les visualiser.

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Leal, Anamary. "Exploring the effectiveness of 3D file browsing techniques for file searching tasks." Honors in the Major Thesis, University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/1285.

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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucf.edu/Systems/DigitalInitiatives/DigitalCollections/InternetDistributionConsentAgreementForm.pdf You may also contact the project coordinator, Kerri Bottorff, at kerri.bottorff@ucf.edu for more information.
Bachelors
Engineering and Computer Science
Early Childhood Education

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Bresso, Emmanuel. "Organisation et exploitation des connaissances sur les réseaux d'intéractions biomoléculaires pour l'étude de l'étiologie des maladies génétiques et la caractérisation des effets secondaires de principes actifs." Thesis, Université de Lorraine, 2013. http://www.theses.fr/2013LORR0122/document.

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La compréhension des pathologies humaines et du mode d'action des médicaments passe par la prise en compte des réseaux d'interactions entre biomolécules. Les recherches récentes sur les systèmes biologiques produisent de plus en plus de données sur ces réseaux qui gouvernent les processus cellulaires. L'hétérogénéité et la multiplicité de ces données rendent difficile leur intégration dans les raisonnements des utilisateurs. Je propose ici des approches intégratives mettant en oeuvre des techniques de gestion de données, de visualisation de graphes et de fouille de données, pour tenter de répondre au problème de l'exploitation insuffisante des données sur les réseaux dans la compréhension des phénotypes associés aux maladies génétiques ou des effets secondaires des médicaments. La gestion des données sur les protéines et leurs propriétés est assurée par un système d'entrepôt de données générique, NetworkDB, personnalisable et actualisable de façon semi-automatique. Des techniques de visualisation de graphes ont été couplées à NetworkDB pour utiliser les données sur les réseaux biologiques dans l'étude de l'étiologie des maladies génétiques entrainant une déficience intellectuelle. Des sous-réseaux de gènes impliqués ont ainsi pu être identifiés et caractérisés. Des profils combinant des effets secondaires partagés par les mêmes médicaments ont été extraits de NetworkDB puis caractérisés en appliquant une méthode de fouille de données relationnelles couplée à Network DB. Les résultats permettent de décrire quelles propriétés des médicaments et de leurs cibles (incluant l'appartenance à des réseaux biologiques) sont associées à tel ou tel profil d'effets secondaires
The understanding of human diseases and drug mechanisms requires today to take into account molecular interaction networks. Recent studies on biological systems are producing increasing amounts of data. However, complexity and heterogeneity of these datasets make it difficult to exploit them for understanding atypical phenotypes or drug side-effects. This thesis presents two knowledge-based integrative approaches that combine data management, graph visualization and data mining techniques in order to improve our understanding of phenotypes associated with genetic diseases or drug side-effects. Data management relies on a generic data warehouse, NetworkDB, that integrates data on proteins and their properties. Customization of the NetworkDB model and regular updates are semi-automatic. Graph visualization techniques have been coupled with NetworkDB. This approach has facilitated access to biological network data in order to study genetic disease etiology, including X-linked intellectual disability (XLID). Meaningful sub-networks of genes have thus been identified and characterized. Drug side-effect profiles have been extracted from NetworkDB and subsequently characterized by a relational learning procedure coupled with NetworkDB. The resulting rules indicate which properties of drugs and their targets (including networks) preferentially associate with a particular side-effect profile

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Li, Yong-Ming, and 李詠銘. "A 3D Dynamic and Interactive Graph Visualization System Based on Physics Laws." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/d83uxh.

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Alsukhni, Mohammad. "Interactive visualization of the collaborative research network." Thesis, 2012. http://hdl.handle.net/10155/207.

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Social networks have been evolving over the past few years, leading to a rapid increase in the number and complexity of relationships among their entities. In this research, we focus on a large scale dataset known as the Digital Bibliography and Library Project or DBLP, which contains information on all publications that have been published in computer and information science related journals and conference proceedings. We model the DBLP dataset as a social network of research collaborations. DBLP is a structured and dynamic dataset stored in the XML file format; it contains over 850,000 authors and 2 million publications, and the resulting collaboration social network is a scale-free network. We define DBLP collaboration social network as a graph that consists of researchers as nodes and links representing the collaboration or co-authorship relationships among the researchers. In this work, we implement a data analysis algorithm called Multidimensional Scaling (MDS) to represent the degree of collaboration among the DBLP authors as Euclidean distances in 2-dimensional space in order to analyze, mine and understand the relational information in this large scale network in a visual way. MDS is a useful technique for data visualization and graph drawing methods, but it has high computational complexity for large scale graphs such as the DBLP graph. Therefore, we propose different solutions to overcome this problem, and improve the MDS performance. In addition, as the quality of the MDS result is measured by a metric known as the stress value, we use the steepest descent method to minimize the stress in an iterative process called stress optimization in order to generate the best geometric layout of the graph nodes in 2-dimensional space. We also propose a solution to further enhance the graph visualization by partitioning the graph into sub-graphs and using repelling forces among nodes within the same sub-graph. Finally, we developed a new visualization tool that can handle the large scale of the DBLP graph, and provides the user a number of significant features that allow them to explore, navigate and sift for information through the graph, such as graph scaling and graphical search functionality.
UOIT

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Alallah, Fouad Shoie. "OA-Graphs: Orientation Agnostic Graphs for improving the legibility of simple visualizations on horizontal displays." 2011. http://hdl.handle.net/1993/4451.

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Horizontal displays, such as tabletop systems, are emerging as the de facto platform for engaging participants in collaborative tasks. Despite significant efforts in improving the interactivity of information on such systems, very little research has been invested in understanding how groups of people view data visualizations in such environments. Numerous studies introduced different techniques to support viewing visualization for groups of people, such as duplicating or reorienting the visual displays. However, when visualizations compete for pixels on the display, prior solutions do not work effectively. In this thesis, I explore whether orientation on horizontal displays impacts the legibility of simple visualizations such as graphs. I have found that users are best at reading a graph when it is right side up, and takes them 20% less time than when it is read upside down. The main objective of this thesis was to investigate whether the readability and understandability of simple graphs can be improved. I have introduced the Orientation Agnostic Graph (OA-Graph) which is legible regardless of orientation. The OA-Graph uses a radial layout which has several interesting properties such as implicit orientation, points equidistant to center, and flexible rearrangement. OA-Graphs perform better than graphs that are presented upside down. I have converted several popular types of graphs into their OA counterpart for improved legibility on tabletop systems. Guidelines are presented that describe how other visualizations can be converted to being orientation agnostic.

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(8802671), Jiaxin Sun. "A software visualization-based approach for understanding and analyzing incremental implementations of complex graph-based algorithms." Thesis, 2020.

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Algorithm has always been a challenging topic for students to learn because of its high level of abstraction. To provide visual aid for algorithm education, many algorithm visualization systems have been designed, developed, and evaluated for the last two decades. However, neither the topics covered nor the interactivity of most AV systems are satisfying. This problem is presented in detail in chapter 2. As a result, this research aims to design, implement and evaluate a compiler-based algorithm visualization system on complex graph algorithm implementation with the assumption that it can help students build both confidence and competence in understanding it. This system is designed and developed according to the method in chapter 3. To test the hypothesis, a comparison experiment on 10 students in the Computer Graphics Technology department is conducted. The complete test protocol can be found in chapter 3.4, and the result can be found in chapter 4. Based on the limited number of subjects’ testing data, a rough conclusion is made that this AV system has only a slight positive effect on subjects’ confidence and competence in understanding complex graph algorithm’s implementation, and its usability is acceptable. However, a concrete conclusion can only be reached if the testing is conducted to a larger group of subjects. In addition to the objective testing data, some interesting subjective observations, which are listed in chapter 5.2 are also made while doing the test. These observations indicate that algorithm visualization may more of a tool to examine users’understanding of the implementation than a tool to help them learn it.

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Royer, Loic. "Unraveling the Structure and Assessing the Quality of Protein Interaction Networks with Power Graph Analysis." Doctoral thesis, 2010. https://tud.qucosa.de/id/qucosa%3A24399.

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Molecular biology has entered an era of systematic and automated experimentation. High-throughput techniques have moved biology from small-scale experiments focused on specific genes and proteins to genome and proteome-wide screens. One result of this endeavor is the compilation of complex networks of interacting proteins. Molecular biologists hope to understand life's complex molecular machines by studying these networks. This thesis addresses tree open problems centered upon their analysis and quality assessment. First, we introduce power graph analysis as a novel approach to the representation and visualization of biological networks. Power graphs are a graph theoretic approach to lossless and compact representation of complex networks. It groups edges into cliques and bicliques, and nodes into a neighborhood hierarchy. We demonstrate power graph analysis on five examples, and show its advantages over traditional network representations. Moreover, we evaluate the algorithm performance on a benchmark, test the robustness of the algorithm to noise, and measure its empirical time complexity at O (e1.71)- sub-quadratic in the number of edges e. Second, we tackle the difficult and controversial problem of data quality in protein interaction networks. We propose a novel measure for accuracy and completeness of genome-wide protein interaction networks based on network compressibility. We validate this new measure by i) verifying the detrimental effect of false positives and false negatives, ii) showing that gold standard networks are highly compressible, iii) showing that authors' choice of confidence thresholds is consistent with high network compressibility, iv) presenting evidence that compressibility is correlated with co-expression, co-localization and shared function, v) showing that complete and accurate networks of complex systems in other domains exhibit similar levels of compressibility than current high quality interactomes. Third, we apply power graph analysis to networks derived from text-mining as well to gene expression microarray data. In particular, we present i) the network-based analysis of genome-wide expression profiles of the neuroectodermal conversion of mesenchymal stem cells. ii) the analysis of regulatory modules in a rare mitochondrial cytopathy: emph{Mitochondrial Encephalomyopathy, Lactic acidosis, and Stroke-like episodes} (MELAS), and iii) we investigate the biochemical causes behind the enhanced biocompatibility of tantalum compared with titanium.

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Dissertations / Theses on the topic 'Interactive graph visualization'

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