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IEEE Pacific visualization Symposium (PacificVis)

作者： Heinsohn, Niklas Gerasch, Andreas Kaufmann, Michael Univ Tubingen Dept Comp Sci Tubingen Germany

ISBN: (纸本)9781479928736

The display of data related to graphical objects on a map is a well studied problem in cartography and several approaches have been published. Adapting the idea of boundary labeling using a focus region, we face the problem of emphasizing additional information and labels for objects within a focus region even when the region might be moving. We propose four different approaches that support effective solutions in various ways, and discuss advantages and drawbacks. Our algorithms regard the dynamic nature of the focus region to place the labels and preserve the mental map of the analyzed drawing. We demonstrate our methods by applying them to biological networks.

关键词： biology computing biological networks boundary labeling methods cartography dynamic focus regions graphical objects mental map Biology Data visualization Force Gaussian distribution Heuristic algorithms Labeling visualization bioinformatics visualization Focus + Context Techniques Visual Knowledge Discovery

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Taxonomy-Based Glyph Design-with a Case Study on Visualizing Workflows of Biological Experiments

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2012年第12期18卷 2603-2612页

作者： Maguire, Eamonn Rocca-Serra, Philippe Sansone, Susanna-Assunta Davies, Jim Chen, Min Univ Oxford Oxford E Res Ctr Oxford OX1 2JD England Univ Oxford Dept Comp Sci Oxford OX1 2JD England

Glyph-based visualization can offer elegant and concise presentation of multivariate information while enhancing speed and ease in visual search experienced by users. As with icon designs, glyphs are usually created based on the designers' experience and intuition, often in a spontaneous manner. Such a process does not scale well with the requirements of applications where a large number of concepts are to be encoded using glyphs. To alleviate such limitations, we propose a new systematic process for glyph design by exploring the parallel between the hierarchy of concept categorization and the ordering of discriminative capacity of visual channels. We examine the feasibility of this approach in an application where there is a pressing need for an efficient and effective means to visualize workflows of biological experiments. By processing thousands of workflow records in a public archive of biological experiments, we demonstrate that a cost-effective glyph design can be obtained by following a process of formulating a taxonomy with the aid of computation, identifying visual channels hierarchically, and defining application-specific abstraction and metaphors.

关键词： Glyph-based techniques taxonomies design methodologies bioinformatics visualization

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Implicit Representation of Molecular Surfaces

Implicit Representation of Molecular Surfaces

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5th IEEE Pacific visualization Symposium

作者： Parulek, Julius Viola, Ivan Univ Bergen Dept Informat N-5020 Bergen Norway

ISBN: (纸本)9781467308649

Molecular surfaces are an established tool to analyze and to study the evolution and interaction of molecules. One of the most advanced representations of molecular surfaces is called the solvent excluded surface. We present a novel and a simple method for representing the solvent excluded surfaces (SES). Our method requires no precomputation and therefore allows us to vary SES parameters outright. We utilize the theory of implicit surfaces and their CSG operations to compose the implicit function representing the molecular surface locally. This function returns a minimal distance to the SES representation. Additionally, negative values of the implicit function determine that the point lies outside SES whereas positive ones that the point lies inside. We describe how to build this implicit function composed of three types of patches constituting the SES representation. Finally, we propose a method to visualize the iso-surface of the implicit function by means of ray-casting and the set of rendering parameters affecting the overall performance.

关键词： visualization of Molecular Surfaces Geometrical Modeling Implicit Surfaces bioinformatics visualization

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Sequence Surveyor: Leveraging Overview for Scalable Genomic Alignment visualization

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2011年第12期17卷 2392-2401页

作者： Albers, Danielle Dewey, Colin Gleicher, Michael Univ Wisconsin Madison WI 53706 USA

In this paper, we introduce overview visualization tools for large-scale multiple genome alignment data. Genome alignment visualization and, more generally, sequence alignment visualization are an important tool for understanding genomic sequence data. As sequencing techniques improve and more data become available, greater demand is being placed on visualization tools to scale to the size of these new datasets. When viewing such large data, we necessarily cannot convey details, rather we specifically design overview tools to help elucidate large-scale patterns. Perceptual science, signal processing theory, and generality provide a framework for the design of such visualizations that can scale well beyond current approaches. We present Sequence Surveyor, a prototype that embodies these ideas for scalable multiple whole-genome alignment overview visualization. Sequence Surveyor visualizes sequences in parallel, displaying data using variable color, position, and aggregation encodings. We demonstrate how perceptual science can inform the design of visualization techniques that remain visually manageable at scale and how signal processing concepts can inform aggregation schemes that highlight global trends, outliers, and overall data distributions as the problem scales. These techniques allow us to visualize alignments with over 100 whole bacterial-sized genomes.

关键词： bioinformatics visualization Perception Theory Scalability Issues Visual Design

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Data repository mapping for influenza protein sequence analysis

Data repository mapping for influenza protein sequence analy...

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Conference on visualization and Data Analysis 2011

作者： Pellegrino, Donald Chen, Chaomei Drexel Univ Coll Informat Sci & Technol Philadelphia PA 19104 USA

ISBN: (纸本)9780819484055

This paper introduces a new method for creating an interactive sequence similarity map of all known influenza virus protein sequences and integrating the map with existing general purpose analytical tools. The NCBI data model was designed to provide a high degree of interconnectedness amongst data objects. Substantial and continuous increase in data volume has led to a large and highly connected information space. Researchers seeking to explore this space are challenged to identify a starting point. They often choose data that is popular in the literature. Reference in the literature follow a power law distribution and popular data points may bias explorers toward paths that lead only to a dead-end of what is already known. To help discover the unexpected we developed an interactive visual analytics system to map the information space of influenza protein sequence data. The design is motivated by the needs of eScience researchers.

关键词： Visual Knowledge Discovery bioinformatics visualization Data Fusion and Integration Data Aggregation

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Integrating cluster formation and cluster evaluation in interactive visual analysis 11

Integrating cluster formation and cluster evaluation in inte...

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Proceedings of the 27th Spring Conference on Computer Graphics

作者： Cagatay Turkay Julius Parulek Nathalie Reuter Helwig Hauser University of Bergen BCCS University of Bergen

ISBN: (纸本)9781450319782

Cluster analysis is a popular method for data investigation where data items are structured into groups called clusters. This analysis involves two sequential steps, namely cluster formation and cluster evaluation. In this paper, we propose the tight integration of cluster formation and cluster evaluation in interactive visual analysis in order to overcome the challenges that relate to the black-box nature of clustering algorithms. We present our conceptual framework in the form of an interactive visual environment. In this realization of our framework, we build upon general concepts such as cluster comparison, clustering tendency, cluster stability and cluster coherence. Additionally, we showcase our framework on the cluster analysis of mixed lipid bilayers.

关键词： bioinformatics visualization data clustering visual knowledge discovery visual analysis models

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Comparative Analysis of Multidimensional, Quantitative Data

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2010年第6期16卷 1027-1035页

作者： Lex, Alexander Streit, Marc Partl, Christian Kashofer, Karl Schmalstieg, Dieter Graz Univ Technol Inst Comp Graph & Vis A-8010 Graz Austria Med Univ Graz Graz Austria

When analyzing multidimensional, quantitative data, the comparison of two or more groups of dimensions is a common task. Typical sources of such data are experiments in biology, physics or engineering, which are conducted in different configurations and use replicates to ensure statistically significant results. One common way to analyze this data is to filter it using statistical methods and then run clustering algorithms to group similar values. The clustering results can be visualized using heat maps, which show differences between groups as changes in color. However, in cases where groups of dimensions have an a priori meaning, it is not desirable to cluster all dimensions combined, since a clustering algorithm can fragment continuous blocks of records. Furthermore, identifying relevant elements in heat maps becomes more difficult as the number of dimensions increases. To aid in such situations, we have developed Matchmaker, a visualization technique that allows researchers to arbitrarily arrange and compare multiple groups of dimensions at the same time. We create separate groups of dimensions which can be clustered individually, and place them in an arrangement of heat maps reminiscent of parallel coordinates. To identify relations, we render bundled curves and ribbons between related records in different groups. We then allow interactive drill-downs using enlarged detail views of the data, which enable in-depth comparisons of clusters between groups. To reduce visual clutter, we minimize crossings between the views. This paper concludes with two case studies. The first demonstrates the value of our technique for the comparison of clustering algorithms. In the second, biologists use our system to investigate why certain strains of mice develop liver disease while others remain healthy, informally showing the efficacy of our system when analyzing multidimensional data containing distinct groups of dimensions.

关键词： Multidimensional data cluster comparison bioinformatics visualization

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Integrating Data Clustering and visualization for the Analysis of 3D Gene Expression Data

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND bioinformatics 2010年第1期7卷 64-79页

作者： Ruebel, Oliver Weber, Gunther H. Huang, Min-Yu Bethel, E. Wes Biggin, Mark D. Fowlkes, Charless C. Hendriks, Cris L. Luengo Keraenen, Soile V. E. Eisen, Michael B. Knowles, David W. Malik, Jitendra Hagen, Hans Hamann, Bernd Univ Calif Berkeley Lawrence Berkeley Lab Computat Res Div Berkeley CA 94720 USA Univ Calif Davis Inst Data Anal & Visualizat Davis CA 95616 USA Univ Kaiserslautern IRTG 1131 D-67653 Kaiserslautern Germany Univ Calif Davis Dept Comp Sci Davis CA 95616 USA Univ Calif Berkeley Lawrence Berkeley Lab Genom Div Berkeley CA 94720 USA Univ Calif Irvine Donald Bren Sch Informat & Comp Sci Irvine CA 92697 USA Swedish Univ Agr Sci Ctr Image Anal SE-75105 Uppsala Sweden Univ Calif Berkeley Howard Hughes Med Inst Berkeley CA 94720 USA Univ Calif Berkeley Dept Mol & Cell Biol Berkeley CA 94720 USA Univ Calif Berkeley Lawrence Berkeley Lab Div Life Sci Berkeley CA 94720 USA Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex data sets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss 1) the integration of data clustering and visualization into one framework, 2) the application of data clustering to 3D gene expression data, 3) the evaluation of the number of clusters k in the context of 3D gene expression clustering, and 4) the improvement of overall analysis quality via dedicated postprocessing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.

关键词： bioinformatics visualization multimodal visualization integrating Infovis/Scivis visual data mining three-dimensional gene expression data clustering cluster visualization gene expression pattern temporal expression variation gene regulation spatial expression pattern

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Using the clustered circular layout as an informative method for visualizing protein-protein interaction networks

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PROTEOMICS 2010年第14期10卷 2723-2727页

作者： Fung, David C. Y. Wilkins, Marc R. Hart, David Hong, Seok-Hee Univ New S Wales Sch Biotechnol & Biomol Sci New S Wales Syst Biol Initiat Sydney NSW 2052 Australia Univ Sydney Sch Informat Technol Sydney NSW 2006 Australia Axogen Proprietary Ltd Eveleigh NSW Australia

The force-directed layout is commonly used in computer-generated visualizations of protein protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.

关键词： bioinformatics visualization Clustered circular layout Force-directed layout Human protein-protein interaction network Visual analytics

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GeneTerrain: Visual exploration of differential gene expression profiles organized in native biomolecular interaction networks

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INFORMATION visualization 2010年第1期9卷 1-12页

作者： You, Qian Fang, Shiaofen Chen, Jake Yue Purdue Univ Sch Sci Dept Comp & Informat Sci Indianapolis IN 46202 USA Purdue Univ Sch Informat Indianapolis IN 46202 USA Indiana Univ Sch Med Ctr Computat Biol & Bioinformat Indianapolis IN USA Indiana Univ Purdue Univ Ctr Biocomp Indianapolis IN 46202 USA

We propose a new network visualization technique using scattered data interpolation and surface rendering, based upon a foundation layout of a scalar field. Contours of the interpolated surfaces are generated to support multi-scale visual interaction for data exploration. Our framework visualizes quantitative attributes of nodes in a network as a continuous surface by interpolating the scalar field, therefore avoiding scalability issues typical in conventional network visualizations while also maintaining the topological properties of the original network. We applied this technique to the study of a bio-molecular interaction network integrated with gene expression data for Alzheimer's Disease (AD). In this application, differential gene expression profiles obtained from the human brain are rendered for AD patients with differing degrees of severity and compared to healthy individuals. We show that this alternative visualization technique is effective in revealing several types of molecular biomarkers, which are traditionally difficult to detect due to 'noises' in data derived from DNA microarray experiments. Information visualization (2010) 9, 1-12. doi: 10.1057/ivs.2008.3

关键词： graph and network visualization bioinformatics visualization visual analytics

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