464 research outputs found
Techniques de bundling : un cas d'étude pour l'exploration de grandes quantités d'informations
We present a fast and simple method to compute bundled layouts of general graphs, dynamic graphs and temporal paths. For this, we first transform a given graph drawing into a density map using kernel density estimation. Next, we apply an image sharpening technique which progressively merges local height maxima by moving the convolved graph edges into the height gradient flow. We show how these techniques can produce simplified visualizations of static, streaming and sequence graphs. We illustrate our techniques with datasets from aircraft monitoring, software engineering, and eye-tracking of static and dynamic scenes
The distinct distribution of two Dictyostelium Talins
Although the distinct distribution of certain molecules along the anterior or posterior edge is essential for directed cell migration, the mechanisms to maintain asymmetric protein localization have not yet been fully elucidated. Here, we studied a mechanism for the distinct localizations of two Dictyostelium talin homologues, talin A and talin B, both of which play important roles in cell migration and adhesion. Using GFP fusion, we found that talin B, as well as its C-terminal actin-binding region, which consists of an I/LWEQ domain and a villin headpiece domain, was restricted to the leading edge of migrating cells. This is in sharp contrast to talin A and its C-terminal actin-binding domain, which co-localized with myosin II along the cell posterior cortex, as reported previously. Intriguingly, even in myosin II-null cells, talin A and its actin-binding domain displayed a specific distribution, co-localizing with stretched actin filaments. In contrast, talin B was excluded from regions rich in stretched actin filaments, although a certain amount of its actin-binding region alone was present in those areas. When cells were sucked by a micro-pipette, talin B was not detected in the retracting aspirated lobe where acto-myosin, talin A, and the actin-binding regions of talin A and talin B accumulated. Based on these results, we suggest that talin A predominantly interacts with actin filaments stretched by myosin II through its C-terminal actin-binding region, while the actin-binding region of talin B does not make such distinctions. Furthermore, talin B appears to have an additional, unidentified mechanism that excludes it from the region rich in stretched actin filaments. We propose that these actin-binding properties play important roles in the anterior and posterior enrichment of talin B and talin A, respectively, during directed cell migration
DEPLOYING, IMPROVING AND EVALUATING EDGE BUNDLING METHODS FOR VISUALIZING LARGE GRAPHS
A tremendous increase in the scale of graphs has been witnessed in a wide range of fields, which demands efficient and effective visualization techniques to assist users in better understandings of large graphs. Conventional node-link diagrams are often used to visualize graphs, whereas excessive edge crossings can easily incur severe visual clutter in the node-link diagram of a large graph. Edge bundling can effectively remedy visual clutter and reveal high-level graph structures. Although significant efforts have been devoted to developing edge bundling, three challenging problems remain. First, edge bundling techniques are often computationally expensive and are not easy to deploy for web-based applications. The state-of-the-art edge bundling methods often require special system supports and techniques such as high-end GPU acceleration for large graphs, which makes these methods less portable, especially for ubiquitous mobile devices. Second, the quantitative quality of edge bundling results is barely assessed in the literature. Currently, the comparison of edge bundling mainly focuses on computational performance and perceptual results. Third, although the family of edge bundling techniques has a rich set of bundling layout, there is a lack of a generic method to generate different styles of edge bundling.
In this research, I aim to address these problems and have made the following contributions. First, I provide an efficient framework to deploy edge bundling for web-based platforms by exploiting standard graphics hardware functions and libraries. My framework can generate high-quality edge bundling results on web-based platforms, and achieve a speedup of 50X compared to the previous state-of-the-art edge bundling method on a graph with half of a million edges. Second, I propose a new moving least squares based approach to lower the algorithm complexity of edge bundling. In addition, my approach can generate better bundling results compared to other methods based on a quality metric. Third, I provide an information-theoretic metric to evaluate the edge bundling methods. I leverage information theory in this metric. With my information-theoretic metric, domain users can choose appropriate edge bundling methods with proper parameters for their applications. Last but not least, I present a deep learning framework for edge bundling visualizations. Through a training process that learns the results of a specific edge bundling method, my deep learning framework can infer the final layout of the edge bundling method. My deep learning framework is a generic framework that can generate the corresponding results of different edge bundling methods.
Adviser: Hongfeng Y
Interactive image-based information visualization for aircraft trajectory analysis
Objectives: The objective of the presented work is to present novel methods for big data
exploration in the Air Traffic Control (ATC) domain. Data is formed by sets of airplane trajectories,
or trails, which in turn records the positions of an aircraft in a given airspace at
several time instants, and additional information such as flight height, speed, fuel consumption,
and metadata (e.g. flight ID). Analyzing and understanding this time-dependent
data poses several non-trivial challenges to information visualization.
Materials and methods: To address this Big Data challenge, we present a set of novel
methods to analyze aircraft trajectories with interactive image-based information visualization
techniques.As a result, we address the scalability challenges in terms of data manipulation
and open questions by presenting a set of related visual analysis methods that focus
on decision-support in the ATC domain. All methods use image-based techniques, in order
to outline the advantages of such techniques in our application context, and illustrated by
means of use-cases from the ATC domain.
Results: For each considered use-case, we outline the type of questions posed by domain
experts, data involved in addressing these questions, and describe the specific image-based
techniques we used to address these questions. Further, for each of the proposed techniques,
we describe the visual representation and interaction mechanisms that have been
used to address the above-mentioned goals. We illustrate these use-cases with real-life
datasets from the ATC domain, and show how our techniques can help end-users in the
ATC domain discover new insights, and solve problems, involving the presented dataset
Organisation of the cytoskeleton of the Drosophila oocyte
In this study, a careful examination was conducted to analyse the actin and microtubule (MT) cytoskeleton organisation during Drosophila oogenesis. We found that at stage 9/10a the actin cytoskeleton at the oocyte cortex is assembled into long bundles, which are essential for anchoring the MT minus-ends at the cortex. The formation of actin bundles requires the function of Profilin. Capu and Spire act downstream of the bundle formation, most likely by anchoring MT minus-ends at the cortex by crosslinking F-actin and MTs. At stage 10b, the actin bundles disassemble and the MT minus-ends are relocated from the actin cortex to subcortical regions. Subsequently, fast ooplasmic streaming is initiated and MTs form parallel arrays at subcortical regions. To identify the regulators of the organisation of the oocyte cytoskeleton, a mutation in a serine/threonine kinase Tao-1, Tao-1No.7 was generated. The analysis of Tao-1No.7 mutants revealed a novel phenotype for the cytoskeleton organisation of the oocyte. In Tao-1No.7 mutant oocytes the cortical actin bundling is disrupted. Unlike in other mutants which affect actin bundling, in Tao-1No.7 oocytes MTs are not forming parallel arrays at subcortical regions; but show high MT density within the entire ooplasm. Thus, the MT network is completely disrupted in Tao-1No.7 oocytes. As a result, the transcripts for the axis determinants are not transported to correct subcellular locations, and as a consequence the embryonic axis is not properly established. The oogenesis phenotypes observed in Tao-1No.7 mutants was rescued by the expression of a Tao-1 cDNA, verifying that Tao-1No.7 is an allele of Tao-1. Nevertheless, a deletion removing the Tao-1 locus completely does not exhibit the defects in the cytoskeletal organisation of the oocyte. Therefore, Tao-1No.7 is most likely a gain of function allele of Tao-1, which shows a phenotype only in a homozygous situation (recessive gain of function)
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