Beyond the horizon: immersive developments for animal ecology research
2023-06-20, Zhang, Ying, Klein, Karsten, Schreiber, Falk, Safi, Kamran
More diverse data on animal ecology are now available. This “data deluge” presents challenges for both biologists and computer scientists; however, it also creates opportunities to improve analysis and answer more holistic research questions. We aim to increase awareness of the current opportunity for interdisciplinary research between animal ecology researchers and computer scientists. Immersive analytics (IA) is an emerging research field in which investigations are performed into how immersive technologies, such as large display walls and virtual reality and augmented reality devices, can be used to improve data analysis, outcomes, and communication. These investigations have the potential to reduce the analysis effort and widen the range of questions that can be addressed. We propose that biologists and computer scientists combine their efforts to lay the foundation for IA in animal ecology research. We discuss the potential and the challenges and outline a path toward a structured approach. We imagine that a joint effort would combine the strengths and expertise of both communities, leading to a well-defined research agenda and design space, practical guidelines, robust and reusable software frameworks, reduced analysis effort, and better comparability of results.
Dynamic Metabolic and Transcriptional Responses of Proteasome-Inhibited Neurons
2023-01-10, Suciu, Ilinca, Delp, Johannes, Gutbier, Simon, Ückert, Anna-Katharina, Spreng, Anna-Sophie, Karreman, Christiaan, Schreiber, Falk, Celardo, Ivana, Amelio, Ivano, Leist, Marcel
Proteasome inhibition is associated with parkinsonian pathology in vivo and degeneration of dopaminergic neurons in vitro. We explored here the metabolome (386 metabolites) and transcriptome (3257 transcripts) regulations of human LUHMES neurons, following exposure to MG-132 [100 nM]. This proteasome inhibitor killed cells within 24 h but did not reduce viability for 12 h. Overall, 206 metabolites were changed in live neurons. The early (3 h) metabolome changes suggested a compromised energy metabolism. For instance, AMP, NADH and lactate were up-regulated, while glycolytic and citric acid cycle intermediates were down-regulated. At later time points, glutathione-related metabolites were up-regulated, most likely by an early oxidative stress response and activation of NRF2/ATF4 target genes. The transcriptome pattern confirmed proteostatic stress (fast up-regulation of proteasome subunits) and also suggested the progressive activation of additional stress response pathways. The early ones (e.g., HIF-1, NF-kB, HSF-1) can be considered a cytoprotective cellular counter-regulation, which maintained cell viability. For instance, a very strong up-regulation of AIFM2 (=FSP1) may have prevented fast ferroptotic death. For most of the initial period, a definite life–death decision was not taken, as neurons could be rescued for at least 10 h after the start of proteasome inhibition. Late responses involved p53 activation and catabolic processes such as a loss of pyrimidine synthesis intermediates. We interpret this as a phase of co-occurrence of protective and maladaptive cellular changes. Altogether, this combined metabolomics–transcriptomics analysis informs on responses triggered in neurons by proteasome dysfunction that may be targeted by novel therapeutic intervention in Parkinson’s disease.
Design considerations for representing systems biology information with the Systems Biology Graphical Notation
2022-08-16, Schreiber, Falk, Czauderna, Tobias
Visual representations are commonly used to explore, analyse, and communicate information and knowledge in systems biology and beyond. Such visualisations not only need to be accurate but should also be aesthetically pleasing and informative. Using the example of the Systems Biology Graphical Notation (SBGN) we will investigate design considerations for graphically presenting information from systems biology, in particular regarding the use of glyphs for types of information, the style of graph layout for network representation, and the concept of bricks for visual network creation.
Immersive Analytics with Abstract 3D Visualizations : a Survey
2022-02, Kraus, Matthias, Fuchs, Johannes, Sommer, Björn, Klein, Karsten, Engelke, Ulrich, Keim, Daniel A., Schreiber, Falk
After a long period of scepticism, more and more publications describe basic research but also practical approaches to howabstract data can be presented in immersive environments for effective and efficient data understanding. Central aspects of thisimportant research question in immersive analytics research are concerned with the use of 3D for visualization, the embeddingin the immersive space, the combination with spatial data, suitable interaction paradigms and the evaluation of use cases.We provide a characterization that facilitates the comparison and categorization of published works and present a survey ofpublications that gives an overview of the state of the art, current trends, and gaps and challenges in current research.
Specifications of standards in systems and synthetic biology: status and developments in 2022 and the COMBINE meeting 2022
2023-03-01, König, Matthias, Gleeson, Padraig, Golebiewski, Martin, Gorochowski, Thomas E., Hucka, Michael, Keating, Sarah M., Myers, Chris J., Nickerson, David P., Sommer, Björn, Schreiber, Falk
This special issue of the Journal of Integrative Bioinformatics contains updated specifications of COMBINE standards in systems and synthetic biology. The 2022 special issue presents three updates to the standards: CellML 2.0.1, SBML Level 3 Package: Spatial Processes, Version 1, Release 1, and Synthetic Biology Open Language (SBOL) Version 3.1.0. This document can also be used to identify the latest specifications for all COMBINE standards. In addition, this editorial provides a brief overview of the COMBINE 2022 meeting in Berlin.
Visual Comparison of Networks in VR
2022-11, Joos, Lucas, Jaeger, Sabrina, Schreiber, Falk, Keim, Daniel A., Klein, Karsten
Networks are an important means for the representation and analysis of data in a variety of research and application areas. While there are many efficient methods to create layouts for networks to support their visual analysis, approaches for the comparison of networks are still underexplored. Especially when it comes to the comparison of weighted networks, which is an important task in several areas, such as biology and biomedicine, there is a lack of efficient visualization approaches. With the availability of affordable high-quality virtual reality (VR) devices, such as head-mounted displays (HMDs), the research field of immersive analytics emerged and showed great potential for using the new technology for visual data exploration. However, the use of immersive technology for the comparison of networks is still underexplored. With this work, we explore how weighted networks can be visually compared in an immersive VR environment and investigate how visual representations can benefit from the extended 3D design space. For this purpose, we develop different encodings for 3D node-link diagrams supporting the visualization of two networks within a single representation and evaluate them in a pilot user study. We incorporate the results into a more extensive user study comparing node-link representations with matrix representations encoding two networks simultaneously. The data and tasks designed for our experiments are similar to those occurring in real-world scenarios. Our evaluation shows significantly better results for the node-link representations, which is contrary to comparable 2D experiments and indicates a high potential for using VR for the visual comparison of networks.
An Intelligent Strategy with All-Atom Molecular Dynamics Simulations for the Design of Lipopeptides against Multidrug-Resistant Pseudomonas aeruginosa
2022-07-28, Jiang, Xukai, Han, Meiling, Tran, Kevin, Patil, Nitin A., Ma, Wendong, Roberts, Kade D., Xiao, Min, Sommer, Bjorn, Schreiber, Falk, Li, Jian
Multidrug-resistant Gram-negative bacteria seriously threaten modern medicine due to the lack of efficacious therapeutic options. Their outer membrane (OM) is an essential protective fortress to exclude many antibiotics. Unfortunately, current structural biology methods are not able to resolve the membrane structure and it is difficult to examine the specific interaction between the OM and small molecules. These limitations hinder mechanistic understanding of antibiotic penetration through the OM and antibiotic discovery. Here, we developed biologically relevant OM models by quantitatively determining membrane lipidomics of Pseudomonas aeruginosa and elucidated how lipopolysaccharide modifications and OM vesicles mediated resistance to polymyxins. Supported by chemical biology and pharmacological assays, our multiscale molecular dynamics simulations provide an intelligent platform to quantify the membrane-penetrating thermodynamics of peptides and predict their antimicrobial activity. Through experimental validations with our in-house polymyxin analogue library, our computational strategy may have significant potential in accelerating the discovery of lipopeptides against bacterial "superbugs".
APL@Voro : Interactive Visualisation and Analysis of Cell Membrane Simulations
2023-02-08, Kern, Martin, Jaeger-Honz, Sabrina, Schreiber, Falk, Sommer, Björn
Molecular dynamics (MD) simulations of cell membranes allow for a better understanding of complex processes such as changing membrane dynamics, lipid rafts and the incorporation/passing of macromolecules into/through membranes. To explore and understand cell membrane compositions, dynamics and processes, visual analytics can help to interpret MD simulation data. APL@Voro is a software for the interactive visualisation and analysis of cell membrane simulations. Here, we present the new APL@Voro, which has been continuously developed since its initial release in 2013. We discuss newly implemented algorithms, methodologies and features, such as the interactive comparison of related simulations and methods to assign lipids to either the upper or lower leaflet.
Towards a hybrid user interface for the visual exploration of large biomolecular networks using virtual reality
2022-10-11, Aichem, Michael, Klein, Karsten, Czauderna, Tobias, Garkov, Dimitar, Zhao, Jinxin, Liu, Jian, Schreiber, Falk
Biomolecular networks, including genome-scale metabolic models (GSMMs), assemble the knowledge regarding the biological processes that happen inside specific organisms in a way that allows for analysis, simulation, and exploration. With the increasing availability of genome annotations and the development of powerful reconstruction tools, biomolecular networks continue to grow ever larger. While visual exploration can facilitate the understanding of such networks, the network sizes represent a major challenge for current visualisation systems. Building on promising results from the area of immersive analytics, which among others deals with the potential of immersive visualisation for data analysis, we present a concept for a hybrid user interface that combines a classical desktop environment with a virtual reality environment for the visual exploration of large biomolecular networks and corresponding data. We present system requirements and design considerations, describe a resulting concept, an envisioned technical realisation, and a systems biology usage scenario. Finally, we discuss remaining challenges.
Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology
2022-07-18, Niarakis, Anna, Waltemath, Dagmar, Glazier, James, Schreiber, Falk, Keating, Sarah M., Nickerson, David, Chaouiya, Claudine, Siegel, Anne, Noël, Vincent, Hermjakob, Henning
Computational models are often employed in systems biology to study the dynamic behaviours of complex systems. With the rise in the number of computational models, finding ways to improve the reusability of these models and their ability to reproduce virtual experiments becomes critical. Correct and effective model annotation in community-supported and standardised formats is necessary for this improvement. Here, we present recent efforts toward a common framework for annotated, accessible, reproducible and interoperable computational models in biology, and discuss key challenges of the field.