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Relational information between different types of entities is often modelled by a multilayer network (MLN) – a network with subnetworks represented by layers. The layers of an MLN can be arranged in different ways in a visual representation, however, the impact of the arrangement on the readability of the network is an open question. Therefore, we studied this impact for several commonly occurring tasks related to MLN analysis. Additionally, layer arrangements with a dimensionality beyond 2D, which are common in this scenario, motivate the use of stereoscopic displays. We ran a human subject study utilising a Virtual Reality headset to evaluate 2D, 2.5D, and 3D layer arrangements. The study employs six analysis tasks that cover the spectrum of an MLN task taxonomy, from path finding and pattern identification to comparisons between and across layers. We found no clear overall winner. However, we explore the task-to-arrangement space and derive empirical-based recommendations on the effective use of 2D, 2.5D, and 3D layer arrangements for MLNs.

Immersive Analytics is concerned with the systematic examination of the benefits and challenges of using immersive environments for data analysis, and the development of corresponding designs that improve the quality and efficiency of the analysis process. While immersive technologies are now broadly available, practical solutions haven’t received broad acceptance in real-world applications outside of several core areas, and proper guidelines on the design of such solutions are still under development. Both fundamental research and applications bring together topics and questions from several fields, and open a wide range of directions regarding underlying theory, evidence from user studies, and practical solutions tailored towards the requirements of application areas. We give an overview on the concepts, topics, research questions, and challenges.

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 aeruginosaand 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”.

Modelling and analysis of metabolic processes is an established research field in Computational Systems Biology and Medicine. There are many different approaches for modelling as well as for visualization, but often these methods ignore the subcellular localization of proteins, enzymes and transporters involved in the metabolic processes.

The Systems Biology Graphical Notation (SBGN) is an emerging standard for the uniform representation of biological processes and networks. By using examples from gene regulation and metabolism, this protocol shows the construction of SBGN maps by either manual drawing or automatic translation using the tool SBGN-ED. In addition, it discusses the enrichment of SBGN maps with different kinds of -omics data to bring numerical data into the context of these networks in order to facilitate the interpretation of experimental data. Finally, the export of such maps to public websites, including clickable images, supports the communication of results within the scientific community. With regard to the described functionalities, other tools partially overlap with SBGN-ED. However, currently, SBGN-ED is the only tool that combines all of these functions, including the representation in SBGN, data mapping and website export. This protocol aims to assist scientists with the step-by-step procedure, which altogether takes ∼90 min.

Ontologies and hierarchical clustering are both important tools in biology and medicine to study high-throughput data such as transcriptomics and metabolomics data. Enrichment of ontology terms in the data is used to identify statistically overrepresented ontology terms, giving insight into relevant biological processes or functional modules. Hierarchical clustering is a standard method to analyze and visualize data to find relatively homogeneous clusters of experimental data points. Both methods support the analysis of the same data set, but are usually considered independently. However, often a combined view is desired: visualizing a large data set in the context of an ontology under consideration of a clustering of the data. This paper proposes a new visualization method for this task.

AbstractDie stetig wachsende Bedeutung von Kulturpflanzen zur Ernährung und zur industriellen Verwendung erfordert es, deren Eigenschaften kontinuierlich zu verbessern. Zur Unterstützung der lebenswissenschaftlichen Forschung in diesem Bereich wurde das Informationssystem MetaCrop entwickelt, welches Daten über metabolische Netzwerke (Pathways) agronomisch bedeutsamer Organismen verwaltet. Der Fokus des Systems liegt neben der ausschließlichen Verwendung manuell kurierter, und damit qualitativ hochwertiger, Informationen auf der hohen Granularität der gespeicherten Daten, mit der versucht wird, die hohe biologische Komplexität der Pflanzen abzubilden. MetaCrop ist unter der URL http://metacrop.ipk-gatersleben.de verfügbar.

Understanding the movement of animals is important for a wide range of scientific interests including migration, disease spread, collective movement behaviour and analysing motion in relation to dynamic changes of the environment such as wind and thermal lifts. Particularly, the three-dimensional (3D) spatial–temporal nature of bird movement data, which is widely available with high temporal and spatial resolution at large volumes, presents a natural option to explore the potential of immersive analytics (IA). We investigate the requirements and benefits of a wide range of immersive environments for explorative visualization and analytics of 3D movement data, in particular regarding design considerations for such 3D immersive environments, and present prototypes for IA solutions. Tailored to biologists studying bird movement data, the immersive solutions enable geo-locational time-series data to be investigated interactively, thus enabling experts to visually explore interesting angles of a flock and its behaviour in the context of the environment. The 3D virtual world presents the audience with engaging and interactive content, allowing users to ‘fly with the flock’, with the potential to ascertain an intuitive overview of often complex datasets, and to provide the opportunity thereby to formulate and at least qualitatively assess hypotheses. This work also contributes to ongoing research efforts to promote better understanding of bird migration and the associated environmental factors at the global scale, thereby providing a visual vehicle for driving public awareness of environmental issues and bird migration patterns.

The article focuses on the works of choreographer Ursina Tossi in Hamburg, Germany, and discusses her dance movements and her role in women empowerment.

Summary: MAVisto is a tool for the exploration of motifs in biological networks. It provides a flexible motif search algorithm and different views for the analysis and visualization of network motifs. These views help to explore interesting motifs: the frequency of motif occurrences can be compared with randomized networks, a list of motifs along with information about structure and number of occurrences depending on the reuse of network elements shows potentially interesting motifs, a motif fingerprint reveals the overall distribution of motifs of a given size and the distribution of a particular motif in the network can be visualized using an advanced layout algorithm. Availability: MAVisto is platform independent and available free of charge as a Java webstart application at http://mavisto.ipk-gatersleben.de/ Contact: schwoebb@ipk-gatersleben.de Supplementary information: Can be found at http://mavisto.ipk-gatersleben.de/