2011 IEEE Symposium on Biological Data Visualization (BioVis).最新文献

The Galaxy Track Browser: Transforming the genome browser from visualization tool to analysis tool 银河轨道浏览器:将基因组浏览器从可视化工具转变为分析工具

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-12-05 DOI: 10.1109/BioVis.2011.6094046

Jeremy Goecks, Kanwei Li, Dave Clements, The Galaxy Team, James Taylor

{"title":"The Galaxy Track Browser: Transforming the genome browser from visualization tool to analysis tool","authors":"Jeremy Goecks, Kanwei Li, Dave Clements, The Galaxy Team, James Taylor","doi":"10.1109/BioVis.2011.6094046","DOIUrl":"https://doi.org/10.1109/BioVis.2011.6094046","url":null,"abstract":"The proliferation of next-generation sequencing (NGS) technologies and analysis tools present new challenges to genome browsers. These challenges include supporting very large datasets, integrating analysis tools with data visualization to help reason about and improve analyses, and sharing or publishing fully interactive visualizations. The Galaxy Track Browser (GTB) is a Web-based genome browser integrated into the Galaxy platform that addresses these challenges. GTB is the first Web-based genome browser to provide a full multi-resolution data model; this model supports efficient data retrieval from very large datasets. GTB leverages the Galaxy platform to combine data visualization and data analysis; users can specify parameter values and run tools to produce new data, all within GTB. GTB also provides interactive filters that dynamically show and hide data and can be used to identify data for further investigation. GTB is available on every Galaxy server, and visualizations can be created for both standard and custom genome builds. Fully interactive GTB visualizations can be shared with colleagues and published on the Web using a simple graphical user interface.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128189133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Parallel Contour-Buildup algorithm for the molecular surface 分子表面的平行轮廓构建算法

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-12-05 DOI: 10.1109/BioVis.2011.6094043

M. Krone, Sebastian Grottel, T. Ertl

{"title":"Parallel Contour-Buildup algorithm for the molecular surface","authors":"M. Krone, Sebastian Grottel, T. Ertl","doi":"10.1109/BioVis.2011.6094043","DOIUrl":"https://doi.org/10.1109/BioVis.2011.6094043","url":null,"abstract":"Molecular Dynamics simulations are an essential tool for many applications. The simulation of large molecules — like proteins — over long trajectories is of high importance e. g. for pharmaceutical, biochemical and medical research. For analyzing these data sets interactive visualization plays a crucial role as details of the interactions of molecules are often affected by the spatial relations between these molecules. From the large range of visual representations for such data, molecule surface representations are of high importance as they clearly depict geometric interactions, such as docking or substrate channel accessibility. However, these surface visualizations are computationally demanding and thus pose a challenge for interactive visualization of time-dependent data sets. We propose an optimization of the Contour-Buildup algorithm for the Solvent Excluded Surface (SES) to remedy this issue. An optimized subdivision of calculation tasks of the original algorithm allows for full utilization of massive parallel processing hardware. Our approach is especially well suited for modern graphics hardware employing the CUDA programming language. As we do not rely on any pre-computations our method is intrinsically applicable to time-dependent data with arbitrarily long trajectories. We are able to visualize the SES for molecules with up to ten thousand atoms interactively on standard consumer graphics cards.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123473517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 37

Visual analysis of next-generation sequencing data to detect overlapping genes in bacterial genomes 下一代测序数据的可视化分析，以检测细菌基因组中的重叠基因

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BIOVIS.2011.6094047

Svenja Simon, Daniela Oelke, Richard Landstorfer, K. Neuhaus, D. Keim

{"title":"Visual analysis of next-generation sequencing data to detect overlapping genes in bacterial genomes","authors":"Svenja Simon, Daniela Oelke, Richard Landstorfer, K. Neuhaus, D. Keim","doi":"10.1109/BIOVIS.2011.6094047","DOIUrl":"https://doi.org/10.1109/BIOVIS.2011.6094047","url":null,"abstract":"Next generation sequencing (NGS) technologies are about to revolutionize biological research. Being able to sequence large amounts of DNA or, indirectly, RNA sequences in a short time period opens numerous new possibilities. However, analyzing the large amounts of data generated in NGS is a serious challenge, which requires novel data analysis and visualization methods to allow the biological experimenter to understand the results. In this paper, we describe a novel system to deal with the flood of data generated by transcriptome sequencing (RNA-seq) using NGS. Our system allows the analyzer to get a quick overview of the data and interactively explore interesting regions based on the three important parameters coverage, transcription, and fit. In particular, our system supports the NGS analysis in the following respects: (1) Representation of the coverage sequence in a way that no artifacts are introduced. (2) Easy determination of a fit of an open reading frame (ORF) to a transcript by mapping the coverage sequence directly into the ORF representation. (3) Providing automatic support for finding interesting regions to address the problems that the overwhelming volume of data comes with. (4) Providing an overview representation that allows parameter tuning and enables quick access to interesting areas of the genome. We show the usefulness of our system by a case study in the area of overlapping gene detection in a bacterial genome.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124522252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Metrics for comparing explicit representations of interconnected biological networks 用于比较相互连接的生物网络的显式表示的度量

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BioVis.2011.6094051

D. Mayerich, C. Björnsson, Jonothan Taylor, B. Roysam

{"title":"Metrics for comparing explicit representations of interconnected biological networks","authors":"D. Mayerich, C. Björnsson, Jonothan Taylor, B. Roysam","doi":"10.1109/BioVis.2011.6094051","DOIUrl":"https://doi.org/10.1109/BioVis.2011.6094051","url":null,"abstract":"One of the major goals in biomedical image processing is accurate segmentation of networks embedded in volumetric data sets. Biological networks are composed of a meshwork of thin filaments that span large volumes of tissue. Examples of these structures include neurons and microvasculature, which can take the form of both hierarchical trees and fully connected networks, depending on the imaging modality and resolution. Network function depends on both the geometric structure and connectivity. Therefore, there is considerable demand for algorithms that segment biological networks embedded in three-dimensional data. While a large number of tracking and segmentation algorithms have been published, most of these do not generalize well across data sets. One of the major reasons for the lack of general-purpose algorithms is the limited availability of metrics that can be used to quantitiatively compare their effectiveness against a pre-constructed ground-truth. In this paper, we propose a robust metric for measuring and visualizing the differences between network models. Our algorithm takes into account both geometry and connectivity to measure network similarity. These metrics are then mapped back onto an explicit model for visualization.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131998756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Visual exploration of microbial populations 微生物种群的视觉探索

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BioVis.2011.6094057

Sara Johansson, J. Johansson, Suzi Adams, Jane Shaw, David Taylor

{"title":"Visual exploration of microbial populations","authors":"Sara Johansson, J. Johansson, Suzi Adams, Jane Shaw, David Taylor","doi":"10.1109/BioVis.2011.6094057","DOIUrl":"https://doi.org/10.1109/BioVis.2011.6094057","url":null,"abstract":"Studies of the ecology of microbial populations are increasingly common within many research areas as the field of microbiomics develops rapidly. The study of the ecology in sampled microbial populations generates high dimensional data sets. Although many analysis methods are available for examination of such data, a tailored tool was required to fulfill the need of interactivity and flexibility for microbiologists. In this paper, MicrobiVis is presented. It is a tool for visual exploration and interactive analysis of micro-biomic populations. MicrobiVis has been designed in close collaboration with end users. It extends previous interactive systems for explorative dimensionality reduction by including a range of domain relevant features. It contributes a flexible and explorative dimensionality reduction as well as a visual and interactive environment for examination of data subsets. By combining information visualization and methods based on analytic tasks common in microbiology as a means for gaining new and relevant insights. The utility of MicrobiVis is demonstrated through a use case describing how a microbiologist may use the system for a visual analysis of a microbial data set. Its usability and potential is indicated through positive feedback from the current end users.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130049225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Visualization of anisotropic contact potentials within protein structures 蛋白质结构内各向异性接触电位的可视化

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BIOVIS.2011.6094045

Corinna Vehlow, B. Preim, M. Lappe

{"title":"Visualization of anisotropic contact potentials within protein structures","authors":"Corinna Vehlow, B. Preim, M. Lappe","doi":"10.1109/BIOVIS.2011.6094045","DOIUrl":"https://doi.org/10.1109/BIOVIS.2011.6094045","url":null,"abstract":"The use of local covalent geometry for quality assessment and refinement of protein structure models is a well-established methodology. The question arises whether information on non-covalent geometry contained within resolved structures can be harnessed to improve structure prediction. Moreover, incorporation of different combinations of priors would pave the way towards multi-body potentials. Existing empirical force-fields do not facilitate an interactive exploration of the parameter space and an assignment of spatial propensities to contacts. Hence, we investigate the possibility of making such propensities available for synergistic modeling. We present an approach that facilitates the extraction and analysis of anisotropic contact potentials for a multitude of parameters describing an amino acid and the conditions within its microenvi-ronment. For this purpose, two novel visualization principles will be introduced. The first visualization illustrates anisotropic residue-dependent contact density potentials in the form of a map projection. A second visualization is overlaid onto this, showing similar local neighborhoods as abstract traces of residues contained within each individual neighborhood. The Contact Geometry Analysis Plugin (CGAP) (for CMView) we developed allows incorporation of geometric orientation propensities into the process of interactive protein modeling and can be used for the generation of improved energy functions. It further supports the analysis of model quality, as it directly illustrates model consistency with known spatial propensities which, in turn, enables users to detect possible structural errors.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131781465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

iHAT: Interactive hierarchical aggregation table 交互式层次聚合表

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BIOVIS.2011.6094049

Corinna Vehlow, Julian Heinrich, F. Battke, D. Weiskopf, K. Nieselt

{"title":"iHAT: Interactive hierarchical aggregation table","authors":"Corinna Vehlow, Julian Heinrich, F. Battke, D. Weiskopf, K. Nieselt","doi":"10.1109/BIOVIS.2011.6094049","DOIUrl":"https://doi.org/10.1109/BIOVIS.2011.6094049","url":null,"abstract":"In the search for single-nucleotide polymorphisms (SNPs), genome wide association studies have become an important technique for the identification of associations between genotype and phenotype of a diverse set of sequence-based data. In this work, we present a methodology for the visual assessment of SNPs using interactive hierarchical aggregation techniques combined with methods known from traditional sequence browsers and cluster heatmaps. Our prototype tool iHAT supports the visualization of multiple sequence alignments, associated metadata, and hierarchical clusterings. Moreover, data-type dependent colormaps and aggregation strategies as well as different filtering options support the user in finding correlations between sequences and metadata. Similar to other visualizations such as parallel coordinates or heatmaps, iHAT is aimed at exploiting the human pattern-recognition ability for spotting patterns that might indicate correlation or anticorrelation. Together with its interactive features and a database backend for fast data retrieval, we consider iHAT as a prototype for a visual analytics system for genome-wide association studies.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130983871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

RuleBender: Integrated visualization for biochemical rule-based modeling RuleBender:基于生化规则建模的集成可视化

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BioVis.2011.6094054

Adam M. Smith, Wen Xu, Yao Sun, J. Faeder, G. Marai

引用次数: 9

Evaluating the VIPER pedigree visualisation: Detecting inheritance inconsistencies in genotyped pedigrees 评估VIPER家系可视化:检测基因型家系的遗传不一致性

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BioVis.2011.6094056

T. Paterson, Martin Graham, J. Kennedy, A. Law

{"title":"Evaluating the VIPER pedigree visualisation: Detecting inheritance inconsistencies in genotyped pedigrees","authors":"T. Paterson, Martin Graham, J. Kennedy, A. Law","doi":"10.1109/BioVis.2011.6094056","DOIUrl":"https://doi.org/10.1109/BioVis.2011.6094056","url":null,"abstract":"VIPER (Visual Pedigree Explorer) is a tool for exploring large complex animal pedigrees and their associated genotype data. The tool combines a novel, space-efficient visualisation of the pedigree structure with an inheritance-checking algorithm. This allows users to explore the apparent errors within the genotype data in the full context of the family and pedigree structure. Ultimately, the aim is to develop an interactive software application that will allow users to identify, confirm and then remove errors from the pedigree structure and scored genotypes. This paper describes an evaluation of how VIPER displays the different scales and types of data set that can occur, along with a description of the further interface functionality necessary to meet the challenges such data presents. This is followed by an examination of a range of possible pedigree genotype errors by replicating these errors in controlled simulated data sets and showing how they are manifested in the VIPER interface and observed by a domain expert. The data sets used include both real and artificially generated data, the advantage of the latter being that they produce known effects in the visualization which the domain expert can then interpret as being useful or unhelpful as they see fit.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133575366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

HiTSEE: A visualization tool for hit selection and analysis in high-throughput screening experiments HiTSEE:在高通量筛选实验中用于命中选择和分析的可视化工具

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BioVis.2011.6094053

E. Bertini, Hendrik Strobelt, J. Braun, O. Deussen, U. Groth, T. Mayer, D. Merhof

引用次数: 7