@article{RigortGuentherHegerletal.2012, author = {Rigort, Alexander and G{\"u}nther, David and Hegerl, Reiner and Baum, Daniel and Weber, Britta and Prohaska, Steffen and Medalia, Ohad and Baumeister, Wolfgang and Hege, Hans-Christian}, title = {Automated segmentation of electron tomograms for a quantitative description of actin filament networks}, series = {Journal of Structural Biology}, volume = {177}, journal = {Journal of Structural Biology}, doi = {10.1016/j.jsb.2011.08.012}, pages = {135 -- 144}, year = {2012}, language = {en} } @misc{LindowBaumHege, author = {Lindow, Norbert and Baum, Daniel and Hege, Hans-Christian}, title = {Atomic Accessibility Radii for Molecular Dynamics Analysis}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-68468}, abstract = {In molecular structure analysis and visualization, the molecule's atoms are often modeled as hard spheres parametrized by their positions and radii. While the atom positions result from experiments or molecular simulations, for the radii typically values are taken from literature. Most often, van der Waals (vdW) radii are used, for which diverse values exist. As a consequence, different visualization and analysis tools use different atomic radii, and the analyses are less objective than often believed. Furthermore, for the geometric accessibility analysis of molecular structures, vdW radii are not well suited. The reason is that during the molecular dynamics simulation, depending on the force field and the kinetic energy in the system, non-bonded atoms can come so close to each other that their vdW spheres intersect. In this paper, we introduce a new kind of atomic radius, called atomic accessibility radius', that better characterizes the accessibility of an atom in a given molecular trajectory. The new radii reflect the movement possibilities of atoms in the simulated physical system. They are computed by solving a linear program that maximizes the radii of the atoms under the constraint that non-bonded spheres do not intersect in the considered molecular trajectory. Using this data-driven approach, the actual accessibility of atoms can be visualized more precisely.}, language = {en} } @inproceedings{LindowBaumHege, author = {Lindow, Norbert and Baum, Daniel and Hege, Hans-Christian}, title = {Atomic Accessibility Radii for Molecular Dynamics Analysis}, series = {Workshop on Molecular Graphics and Visual Analysis of Molecular Data}, booktitle = {Workshop on Molecular Graphics and Visual Analysis of Molecular Data}, publisher = {The Eurographics Association}, isbn = {978-3-03868-061-1}, doi = {10.2312/molva.20181101}, abstract = {In molecular structure analysis and visualization, the molecule's atoms are often modeled as hard spheres parametrized by their positions and radii. While the atom positions result from experiments or molecular simulations, for the radii typically values are taken from literature. Most often, van der Waals (vdW) radii are used, for which diverse values exist. As a consequence, different visualization and analysis tools use different atomic radii, and the analyses are less objective than often believed. Furthermore, for the geometric accessibility analysis of molecular structures, vdW radii are not well suited. The reason is that during the molecular dynamics simulation, depending on the force field and the kinetic energy in the system, non-bonded atoms can come so close to each other that their vdW spheres intersect. In this paper, we introduce a new kind of atomic radius, called atomic accessibility radius', that better characterizes the accessibility of an atom in a given molecular trajectory. The new radii reflect the movement possibilities of atoms in the simulated physical system. They are computed by solving a linear program that maximizes the radii of the atoms under the constraint that non-bonded spheres do not intersect in the considered molecular trajectory. Using this data-driven approach, the actual accessibility of atoms can be visualized more precisely.}, language = {en} } @article{MikulaDoerffelBaumetal.2022, author = {Mikula, Natalia and D{\"o}rffel, Tom and Baum, Daniel and Hege, Hans-Christian}, title = {An Interactive Approach for Identifying Structure Definitions}, series = {Computer Graphics Forum}, volume = {41}, journal = {Computer Graphics Forum}, number = {3}, doi = {10.1111/cgf.14543}, pages = {321 -- 332}, year = {2022}, abstract = {Our ability to grasp and understand complex phenomena is essentially based on recognizing structures and relating these to each other. For example, any meteorological description of a weather condition and explanation of its evolution recurs to meteorological structures, such as convection and circulation structures, cloud fields and rain fronts. All of these are spatiotemporal structures, defined by time-dependent patterns in the underlying fields. Typically, such a structure is defined by a verbal description that corresponds to the more or less uniform, often somewhat vague mental images of the experts. However, a precise, formal definition of the structures or, more generally, concepts is often desirable, e.g., to enable automated data analysis or the development of phenomenological models. Here, we present a systematic approach and an interactive tool to obtain formal definitions of spatiotemporal structures. The tool enables experts to evaluate and compare different structure definitions on the basis of data sets with time-dependent fields that contain the respective structure. Since structure definitions are typically parameterized, an essential part is to identify parameter ranges that lead to desired structures in all time steps. In addition, it is important to allow a quantitative assessment of the resulting structures simultaneously. We demonstrate the use of the tool by applying it to two meteorological examples: finding structure definitions for vortex cores and center lines of temporarily evolving tropical cyclones. Ideally, structure definitions should be objective and applicable to as many data sets as possible. However, finding such definitions, e.g., for the common atmospheric structures in meteorology, can only be a long-term goal. The proposed procedure, together with the presented tool, is just a first systematic approach aiming at facilitating this long and arduous way.}, language = {en} } @article{LindowBaumProhaskaetal.2010, author = {Lindow, Norbert and Baum, Daniel and Prohaska, Steffen and Hege, Hans-Christian}, title = {Accelerated Visualization of Dynamic Molecular Surfaces}, series = {Comput. Graph. Forum}, volume = {29}, journal = {Comput. Graph. Forum}, doi = {10.1111/j.1467-8659.2009.01693.x}, pages = {943 -- 952}, year = {2010}, language = {en} } @article{VohraHarthIsoeetal., author = {Vohra, Sumit Kumar and Harth, Philipp and Isoe, Yasuko and Bahl, Armin and Fotowat, Haleh and Engert, Florian and Hege, Hans-Christian and Baum, Daniel}, title = {A Visual Interface for Exploring Hypotheses about Neural Circuits}, series = {IEEE Transactions on Visualization and Computer Graphics}, journal = {IEEE Transactions on Visualization and Computer Graphics}, doi = {10.1109/TVCG.2023.3243668}, abstract = {One of the fundamental problems in neurobiological research is to understand how neural circuits generate behaviors in response to sensory stimuli. Elucidating such neural circuits requires anatomical and functional information about the neurons that are active during the processing of the sensory information and generation of the respective response, as well as an identification of the connections between these neurons. With modern imaging techniques, both morphological properties of individual neurons as well as functional information related to sensory processing, information integration and behavior can be obtained. Given the resulting information, neurobiologists are faced with the task of identifying the anatomical structures down to individual neurons that are linked to the studied behavior and the processing of the respective sensory stimuli. Here, we present a novel interactive tool that assists neurobiologists in the aforementioned task by allowing them to extract hypothetical neural circuits constrained by anatomical and functional data. Our approach is based on two types of structural data: brain regions that are anatomically or functionally defined, and morphologies of individual neurons. Both types of structural data are interlinked and augmented with additional information. The presented tool allows the expert user to identify neurons using Boolean queries. The interactive formulation of these queries is supported by linked views, using, among other things, two novel 2D abstractions of neural circuits. The approach was validated in two case studies investigating the neural basis of vision-based behavioral responses in zebrafish larvae. Despite this particular application, we believe that the presented tool will be of general interest for exploring hypotheses about neural circuits in other species, genera and taxa.}, language = {en} } @misc{VohraHarthIsoeetal., author = {Vohra, Sumit Kumar and Harth, Philipp and Isoe, Yasuko and Bahl, Armin and Fotowat, Haleh and Engert, Florian and Hege, Hans-Christian and Baum, Daniel}, title = {A Visual Interface for Exploring Hypotheses about Neural Circuits}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-89932}, abstract = {One of the fundamental problems in neurobiological research is to understand how neural circuits generate behaviors in response to sensory stimuli. Elucidating such neural circuits requires anatomical and functional information about the neurons that are active during the processing of the sensory information and generation of the respective response, as well as an identification of the connections between these neurons. With modern imaging techniques, both morphological properties of individual neurons as well as functional information related to sensory processing, information integration and behavior can be obtained. Given the resulting information, neurobiologists are faced with the task of identifying the anatomical structures down to individual neurons that are linked to the studied behavior and the processing of the respective sensory stimuli. Here, we present a novel interactive tool that assists neurobiologists in the aforementioned task by allowing them to extract hypothetical neural circuits constrained by anatomical and functional data. Our approach is based on two types of structural data: brain regions that are anatomically or functionally defined, and morphologies of individual neurons. Both types of structural data are interlinked and augmented with additional information. The presented tool allows the expert user to identify neurons using Boolean queries. The interactive formulation of these queries is supported by linked views, using, among other things, two novel 2D abstractions of neural circuits. The approach was validated in two case studies investigating the neural basis of vision-based behavioral responses in zebrafish larvae. Despite this particular application, we believe that the presented tool will be of general interest for exploring hypotheses about neural circuits in other species, genera and taxa.}, language = {en} } @inproceedings{HarthVohraUdvaryetal., author = {Harth, Philipp and Vohra, Sumit and Udvary, Daniel and Oberlaender, Marcel and Hege, Hans-Christian and Baum, Daniel}, title = {A Stratification Matrix Viewer for Analysis of Neural Network Data}, series = {Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM)}, booktitle = {Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM)}, address = {Vienna, Austria}, doi = {10.2312/vcbm.20221194}, abstract = {The analysis of brain networks is central to neurobiological research. In this context the following tasks often arise: (1) understand the cellular composition of a reconstructed neural tissue volume to determine the nodes of the brain network; (2) quantify connectivity features statistically; and (3) compare these to predictions of mathematical models. We present a framework for interactive, visually supported accomplishment of these tasks. Its central component, the stratification matrix viewer, allows users to visualize the distribution of cellular and/or connectional properties of neurons at different levels of aggregation. We demonstrate its use in four case studies analyzing neural network data from the rat barrel cortex and human temporal cortex.}, language = {en} } @inproceedings{BaumHege2006, author = {Baum, Daniel and Hege, Hans-Christian}, title = {A Point-matching based algorithm for 3D surface alignment of drug-sized molecules}, series = {Computational Life Sciences II, Second International Symposium, CompLife 2006, Cambridge (UK), Sept. 2006}, volume = {4216}, booktitle = {Computational Life Sciences II, Second International Symposium, CompLife 2006, Cambridge (UK), Sept. 2006}, publisher = {Springer}, doi = {10.1007/11875741_18}, pages = {183 -- 193}, year = {2006}, language = {en} }