Browsing by Author "Linares, Mathieu"

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    Level of Detail Exploration of Electronic Transition Ensembles using Hierarchical Clustering
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Sidwall Thygesen, Signe; Masood, Talha Bin; Linares, Mathieu; Natarajan, Vijay; Hotz, Ingrid; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    We present a pipeline for the interactive visual analysis and exploration of molecular electronic transition ensembles. Each ensemble member is specified by a molecular configuration, the charge transfer between two molecular states, and a set of physical properties. The pipeline is targeted towards theoretical chemists, supporting them in comparing and characterizing electronic transitions by combining automatic and interactive visual analysis. A quantitative feature vector characterizing the electron charge transfer serves as the basis for hierarchical clustering as well as for the visual representations. The interface for the visual exploration consists of four components. A dendrogram provides an overview of the ensemble. It is augmented with a level of detail glyph for each cluster. A scatterplot using dimensionality reduction provides a second visualization, highlighting ensemble outliers. Parallel coordinates show the correlation with physical parameters. A spatial representation of selected ensemble members supports an in-depth inspection of transitions in a form that is familiar to chemists. All views are linked and can be used to filter and select ensemble members. The usefulness of the pipeline is shown in three different case studies.
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    MolFind - Integrated Multi-Selection Schemes for Complex Molecular Structures
    (The Eurographics Association, 2019) Skånberg, Robin; Linares, Mathieu; Falk, Martin; Hotz, Ingrid; Ynnerman, Anders; Byska, Jan and Krone, Michael and Sommer, Björn
    Selecting components and observing changes of properties and configurations over time is an important step in the analysis of molecular dynamics (MD) data. In this paper, we present a selection tool combining text-based queries with spatial selection and filtering. Morphological operations facilitate refinement of the selection by growth operators, e.g. across covalent bonds. The combination of different selection paradigms enables flexible and intuitive analysis on different levels of detail and visual depiction of molecular events. Immediate visual feedback during interactions ensures a smooth exploration of the data. We demonstrate the utility of our selection framework by analyzing temporal changes in the secondary structure of poly-alanine and the binding of aspirin to phospholipase A2.