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Now showing 1 - 10 of 22
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    A Web-based Visual Analytics Application for Biological Networks
    (The Eurographics Association, 2020) Krone, Michael; Dräger, Andreas; Cobanoglu, Ebru; Harke, Manuel Otto; Hoene, Miriam; Weigert, Cora; Lehmann, Rainer; Byška, Jan and Jänicke, Stefan
    Modern high-throughput methods enable rapidly obtaining transcriptomics data, which includes information about the expression rate of genes. The expression rates are usually given as fold change, which describes the over- or under-expression of each gene. Each gene can be part of one or more biological pathways. A pathway models the interactions between molecules in an organism that lead to a particular chemical change. Consequently, many applications in medical research need to analyze the impact of gene expression changes on the biological pathways of an organism. It allows concluding diseases or other conditions of the organism. We present a web-based visual analytics application that facilitates exploring the network of biological pathways corresponding to a given set of genes. The network is constructed from pathways derived from an external database. Users can interactively zoom and filter the network and get details on demand. Our application is currently work in progress and is developed in close collaboration with medical researchers. In subsequent steps, we strive to add more features, such as the ability to compare data from different individuals or to visualize time series data. Furthermore, we want to extend our application to visualize not just transcriptomics but multi-omics data.
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    MolVa 2020: Frontmatter
    (The Eurographics Association, 2020) Byška, Jan; Krone, Michael; Sommer, Björn; Byška, Jan and Krone, Michael and Sommer, Björn
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    Visual Analysis of Multivariate Intensive Care Surveillance Data
    (The Eurographics Association, 2020) Brich, Nicolas; Schulz, Christoph; Peter, Jörg; Klingert, Wilfried; Schenk, Martin; Weiskopf, Daniel; Krone, Michael; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
    We present an approach for visual analysis of high-dimensional measurement data with varying sampling rates in the context of an experimental post-surgery study performed on a porcine surrogate model. The study aimed at identifying parameters suitable for diagnosing and prognosticating the volume state-a crucial and difficult task in intensive care medicine. In intensive care, most assessments not only depend on a single measurement but a plethora of mixed measurements over time. Even for trained experts, efficient and accurate analysis of such multivariate time-dependent data remains a challenging task. We present a linked-view post hoc visual analysis application that reduces data complexity by combining projection-based time curves for overview with small multiples for details on demand. Our approach supports not only the analysis of individual patients but also the analysis of ensembles by adapting existing techniques using non-parametric statistics. We evaluated the effectiveness and acceptance of our application through expert feedback with domain scientists from the surgical department using real-world data: the results show that our approach allows for detailed analysis of changes in patient state while also summarizing the temporal development of the overall condition. Furthermore, the medical experts believe that our method can be transferred from medical research to the clinical context, for example, to identify the early onset of a sepsis.
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    MolVa 2021: Frontmatter
    (The Eurographics Association, 2021) Byška, Jan; Krone, Michael; Sommer, Björn; Byška, Jan and Krone, Michael and Sommer, Björn
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    VisGap 2020: Frontmatter
    (The Eurographics Association, 2020) Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas; Gillmann, Christina and Krone, Michael and Reina, Guido and Wischgoll, Thomas
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    visMOP - A Visual Analytics Approach for Multi-omics Pathways
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Brich, Nicolas; Schacherer, Nadine; Hoene, Miriam; Weigert, Cora; Lehmann, Rainer; Krone, Michael; Bujack, Roxana; Archambault, Daniel; Schreck, Tobias
    We present an approach for the visual analysis of multi-omics data obtained using high-throughput methods. The term ''omics'' denotes measurements of different types of biologically relevant molecules, like the products of gene transcription (transcriptomics) or the abundance of proteins (proteomics). Current popular visualization approaches often only support analyzing each of these omics separately. This, however, disregards the interconnectedness of different biologically relevant molecules and processes. Consequently, it describes the actual events in the organism suboptimally or only partially. Our visual analytics approach for multi-omics data provides a comprehensive overview and details-on-demand by integrating the different omics types in multiple linked views. To give an overview, we map the measurements to known biological pathways and use a combination of a clustered network visualization, glyphs, and interactive filtering. To ensure the effectiveness and utility of our approach, we designed it in close collaboration with domain experts and assessed it using an exemplary workflow with real-world transcriptomics, proteomics, and lipidomics measurements from mice.
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    MolVa 2023: Frontmatter
    (The Eurographics Association, 2023) Byška, Jan; Krone, Michael; Sommer, Björn; Byška, Jan; Krone, Michael; Sommer, Björn
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    VisGap 2024: Frontmatter
    (The Eurographics Association, 2024) Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas; Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas
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    State of the Art of Molecular Visualization in Immersive Virtual Environments
    (© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Kuťák, David; Vázquez, Pere‐Pau; Isenberg, Tobias; Krone, Michael; Baaden, Marc; Byška, Jan; Kozlíková, Barbora; Miao, Haichao; Hauser, Helwig and Alliez, Pierre
    Visualization plays a crucial role in molecular and structural biology. It has been successfully applied to a variety of tasks, including structural analysis and interactive drug design. While some of the challenges in this area can be overcome with more advanced visualization and interaction techniques, others are challenging primarily due to the limitations of the hardware devices used to interact with the visualized content. Consequently, visualization researchers are increasingly trying to take advantage of new technologies to facilitate the work of domain scientists. Some typical problems associated with classic 2D interfaces, such as regular desktop computers, are a lack of natural spatial understanding and interaction, and a limited field of view. These problems could be solved by immersive virtual environments and corresponding hardware, such as virtual reality head‐mounted displays. Thus, researchers are investigating the potential of immersive virtual environments in the field of molecular visualization. There is already a body of work ranging from educational approaches to protein visualization to applications for collaborative drug design. This review focuses on molecular visualization in immersive virtual environments as a whole, aiming to cover this area comprehensively. We divide the existing papers into different groups based on their application areas, and types of tasks performed. Furthermore, we also include a list of available software tools. We conclude the report with a discussion of potential future research on molecular visualization in immersive environments.
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    VisGap 2021: Frontmatter
    (The Eurographics Association, 2021) Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas; Gillmann, Christina and Krone, Michael and Reina, Guido and Wischgoll, Thomas