5.7
Network visualization and interaction
One of the most important parts in biological network modeling is the representation of knowl- edge, data, and results. The aim of VANESA is to support biological scientists working at the bench. Data in different kinds of formats has to be transformed into pictures that can be in- terpreted by human beings. Solving a problem means not only to calculating results. It means representing results so that the solution is transparent and understandable. Results need to be rearranged to lead insights into a collection of data. The resulting representation needs to be simple in order to efficiently encode data.
In order to develop a simple and efficient user interface for VANESA, scientist’s experiences and interactions were studied. The focus of the user interface design and human-system interaction is the reconstruction and analysis of biological networks at hand, without drawing unnecessary attention to the operational process. Therefore, a balance between technical functionality and visual elements had to be found to create a graphical user interface that is operational, usable, and adaptable to changing user needs. As a guideline for the design process, the concepts defined in the EN ISO 92413 standard for ergonomics of human-system interaction were used,
particularly the sub-sections 10-14 for the design of dialogues between humans and information systems. Additionally to the EN ISO 9241 standard, there were many meaningful discussions with scientists from the laboratory to discern what users aim to do with biological networks and how the system should coincide with given research activities. A lot of prototyping and usability testing was necessary to get a good understanding of scientist’s needs.
To see how visually presented information may affect people’s understanding, special attention was paid to how researchers perceive, think about, and interact with biological graphs. The complexity of data can make analysis a challenging task. Scientific visualization must assist researchers in data analysis and speed up progress in having visual access to large quantities of data. Visualization can provide valuable assistance for data analysis and decision-making tasks [Fry08, TM04].
Therefore, experiences have been gained on eye-tracking in graph layout visualization, visual acuity, surrounding items, and color scales. These factors were studied as a basis for graph layout design (see Figure 5.15) to determine what catches the user’s attention. Neuromorphic models were used to identify elements of a visual scene that are likely to attract attention. The iLab Neuromorphic Vision toolkit4 was used for this purpose, which is based on the theory of
computational modeling of visual attention [IK01]. As model input, different kinds of biological networks, as well as different networks sizes were tested. The neuromorphic model studies provide valuable insight into when, why, and whether specific visualization techniques provide effective cognitive support.
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http://www.iso.org 4
Figure 5.15: This figure shows one computational neuromorphic model study for the informa- tion visualization design of VANESA (A). During the study, the effect of color, intensity, and orientation on a middle-sized protein-protein interaction network was analyzed (B). The results have been used to provide valuable insights into why, when, and whether specific visualization techniques provide effective cognitive support for human observers. The aim was to find visu- alization techniques that assist researchers with cognitive support in providing information of the most relevant objects within biological networks. The starting point was the investigation of how to visually guide users in detecting the most important network motifs and elements within a graph.
116 5.7. Network visualization and interaction
Figure 5.16: This figure shows how an inverted background and foreground increases contrast and the visual appearance of a network model. Users are able to focus better on network structures and model elements.
It was discovered that users get tired of examining a biological network after a certain time. Their eyes become stressed and their concentration decreases because of the size and complexity of data. The contrast between white background and black network visualizations particularly makes it difficult to focus on certain elements. A white background can become very aggressive after several minutes. Therefore, a function has been implemented which inverts background and foreground. Using a black background and grey network representation, users feel more comfortable and are able to identify structures and important elements much easier (see Fig- ure 5.16). Besides, they spent more time on analysis and are more active in the interactive exploration of the system. Shades, contrasts, transparency, size, and network layout also make information more visually accessible. Especially network visualization is of great importance. Although the JUNG library offers several layouts, they are not appropriate for arranging large and complex networks. Therefore, an external java library was integrated, which includes a spring-embedded layout called GEM Layout [FLM94]. This network layout makes it possible to minimize edge crossing, edge breaks, considers node distance, min/max size of nodes, edge length, and tries to build up symmetry. This layout is always applied when users automatically reconstruct biological networks from database content.
Furthermore, VANESA supports zoom-in and zoom-out functions to aid in examining certain details. Rotate and stretch functions make the network interaction even more convenient. As biological networks can be large in dimension and size, an additional visualization viewer acts
Figure 5.17: Selected elements within a biological network are highlighted in VANESA. This enables users to focus on important elements, rather than being overwhelmed with the whole network complexity.
as a satellite view, which helps users orient themselves in the model. In the satellite view, the full graph is always visible and all mouse actions affect the network in the main panel. A rectangular shape in the satellite view shows the visible bounds of the main panel. To make the interaction more intuitive, a search form enables users to find network elements. Therefore, an additional panel lists all network elements within the network. The elements are ordered by name and can be selected with a mouse click. Using this list, users can intuitively search for elements of interest and automatically center them in an animated way in the main panel. As a reconstructed biological model can consist of many different elements from various -omic levels, different elements can be displayed or hidden in the network representation in order to increase the clarity of the network representation. Thus, users have the possibility to focus on particular elements before going into the overall context of the model (see Figure 5.17). Furthermore, users can adopt the network representation. Each biological element has its own characteristics. VANESA offers a specialized form for each of the biological compounds, in which users can specify identifier, name, description, synonyms, and structural information, among others. Node color and shape can be also changed in order to highlight selected elements within the network. It is even possible to draw an entire cell and to place the network elements on drawn compartments, such as cell membrane, nucleus, and others.