DSpace Repository :: Browsing by Author "Krone, Michael"

Browsing by Author "Krone, Michael"

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Analyzing Protein Similarity by Clustering Molecular Surface Maps
(The Eurographics Association, 2020) Schatz, Karsten; Frieß, Florian; Schäfer, Marco; Ertl, Thomas; Krone, Michael; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
Many biochemical and biomedical applications like protein engineering or drug design are concerned with finding functionally similar proteins, however, this remains to be a challenging task. We present a new imaged-based approach for identifying and visually comparing proteins with similar function that builds on the hierarchical clustering of Molecular Surface Maps. Such maps are two-dimensional representations of complex molecular surfaces and can be used to visualize the topology and different physico-chemical properties of proteins. Our method is based on the idea that visually similar maps also imply a similarity in the function of the mapped proteins. To determine map similarity we compute descriptive feature vectors using image moments, color moments, or a Convolutional Neural Network and use them for a hierarchical clustering of the maps. We show that image similarity as found by our clustering corresponds to functional similarity of mapped proteins by comparing our results to the BRENDA database, which provides a hierarchical function-based annotation of enzymes. We also compare our results to the TM-score, which is a similarity value for pairs of arbitrary proteins. Our visualization prototype supports the entire workflow from map generation, similarity computing to clustering and can be used to interactively explore and analyze the results.
EuroVis 2022 Posters: Frontmatter
(The Eurographics Association, 2022) Krone, Michael; Lenti, Simone; Schmidt, Johanna; Krone, Michael; Lenti, Simone; Schmidt, Johanna
Interactive CPU-based Ray Tracing of Solvent Excluded Surfaces
(The Eurographics Association, 2019) Rau, Tobias; Zahn, Sebastian; Krone, Michael; Reina, Guido; Ertl, Thomas; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
Depictions of molecular surfaces such as the Solvent Excluded Surface (SES) can provide crucial insight into functional molecular properties, such as the molecule's potential to react. The interactive visualization of single and multiple molecule surfaces is essential for the data analysis by domain experts. Nowadays, the SES can be rendered at high frame rates using shader-based ray casting on the GPU. However, rendering large molecules or larger molecule complexes requires large amounts of memory that has the potential to exceed the memory limitations of current hardware. Here we show that rendering using CPU ray tracing also reaches interactive frame rates without hard limitations to memory. In our results large molecule complexes can be rendered with only the precomputation of each individual SES, and no further involved representation or transformation. Additionally, we provide advanced visualization techniques like ambient occlusion opacity mapping (AOOM) to enhance the comprehensibility of the molecular structure. CPU ray tracing not only provides very high image quality and global illumination, which is beneficial for the perception of spatial structures, it also opens up the possibility to visualize larger data sets and to render on any HPC cluster. Our results demonstrate that simple instancing of geometry keeps the memory consumption for rendering large molecule complexes low, so the examination of much larger data is also possible.
A Massively Parallel CUDA Algorithm to Compute and Visualize the Solvent Excluded Surface for Dynamic Molecular Data
(The Eurographics Association, 2019) Schäfer, Marco; Krone, Michael; Byska, Jan and Krone, Michael and Sommer, Björn
The interactive visualization of molecular surfaces can help users to understand the dynamic behavior of proteins in molecular dynamics simulations. These simulations play an important role in biochemical and pharmaceutical research, e.g. in drug design. The efficient calculation of molecular surfaces in a fast and memory-saving way is a challenging task. For example, to gain a detailed understanding of complex diseases like Alzheimer, conformational changes and spatial interactions between molecules have to be investigated. Molecular surfaces, such as Solvent Excluded Surfaces (SES), are instrumental for identifying structures such as tunnels or cavities that critically influence transport processes and docking events, which might induce enzymatic reactions. Therefore, we developed a highly parallelized algorithm that exploits the massive computing power of modern graphics hardware. Our analytical algorithm is suitable for the real-time computation of dynamic SES based on many time steps, as it runs interactively on a single consumer GPU for more than 20 k atoms.
Molecular Sombreros: Abstract Visualization of Binding Sites within Proteins
(The Eurographics Association, 2019) Schatz, Karsten; Krone, Michael; Bauer, Tabea L.; Ferrario, Valerio; Pleiss, Jürgen; Ertl, Thomas; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
We present a novel abstract visualization for the binding sites of proteins. Binding sites play an essential role in enzymatic reactions and are, thus, often investigated in structural biology. They are typically located within cavities. The shape and properties of the cavity influence whether and how easily a substrate can reach the active site where the reaction is triggered. Molecular surface visualizations can help to analyze the accessibility of binding sites, but are typically prone to visual clutter. Our novel abstract visualization shows the cavity containing the binding site as well as the surface region directly surrounding the cavity entrance in a simplified manner. The resulting visualization resembles a hat, where the brim depicts the surrounding surface region and the crown the cavity. Hence, we dubbed our abstraction Molecular Sombrero, using the Spanish term for 'hat'. Our abstraction is less cluttered than traditional molecular surface visualizations. It highlights important parameters, like cavity diameter, by mapping them to the shape of the sombrero. The visual abstraction also facilitates an easy side-by-side comparison of different data sets. We show the applicability of our Molecular Sombreros to different real-world use cases.
VCBM 2020: Frontmatter
(The Eurographics Association, 2020) Kozlíková, Barbora; Krone, Michael; Smit, Noeska; Nieselt, Kay; Raidou, Renata Georgia; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
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
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
VisGap 2023: Frontmatter
(The Eurographics Association, 2023) Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas; Gillmann, Christina; Krone, Michael; Reina, Guido; Wischgoll, Thomas
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.
Visual Analysis of Large‐Scale Protein‐Ligand Interaction Data
(© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2021) Schatz, Karsten; Franco‐Moreno, Juan José; Schäfer, Marco; Rose, Alexander S.; Ferrario, Valerio; Pleiss, Jürgen; Vázquez, Pere‐Pau; Ertl, Thomas; Krone, Michael; Benes, Bedrich and Hauser, Helwig
When studying protein‐ligand interactions, many different factors can influence the behaviour of the protein as well as the ligands. Molecular visualisation tools typically concentrate on the movement of single ligand molecules; however, viewing only one molecule can merely provide a hint of the overall behaviour of the system. To tackle this issue, we do not focus on the visualisation of the local actions of individual ligand molecules but on the influence of a protein and their overall movement. Since the simulations required to study these problems can have millions of time steps, our presented system decouples visualisation and data preprocessing: our preprocessing pipeline aggregates the movement of ligand molecules relative to a receptor protein. For data analysis, we present a web‐based visualisation application that combines multiple linked 2D and 3D views that display the previously calculated data The central view, a novel enhanced sequence diagram that shows the calculated values, is linked to a traditional surface visualisation of the protein. This results in an interactive visualisation that is independent of the size of the underlying data, since the memory footprint of the aggregated data for visualisation is constant and very low, even if the raw input consisted of several terabytes.
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.

Browsing by Author "Krone, Michael"

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