2011 IEEE Symposium on Biological Data Visualization (BioVis).最新文献_第2页

Fiber stippling: An illustrative rendering for probabilistic diffusion tractography 纤维点画:概率扩散导管成像的说明性渲染

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BioVis.2011.6094044

Mathias Goldau, Alexander Wiebel, Nico S. Gorbach, C. Melzer, M. Hlawitschka, G. Scheuermann, M. Tittgemeyer

{"title":"Fiber stippling: An illustrative rendering for probabilistic diffusion tractography","authors":"Mathias Goldau, Alexander Wiebel, Nico S. Gorbach, C. Melzer, M. Hlawitschka, G. Scheuermann, M. Tittgemeyer","doi":"10.1109/BioVis.2011.6094044","DOIUrl":"https://doi.org/10.1109/BioVis.2011.6094044","url":null,"abstract":"One of the most promising avenues for compiling anatomical brain connectivity data arises from diffusion magnetic resonance imaging (dMRI). dMRI provides a rather novel family of medical imaging techniques with broad application in clinical as well as basic neu-roscience as it offers an estimate of the brain's fiber structure completely non-invasively and in vivo. A convenient way to reconstruct neuronal fiber pathways and to characterize anatomical connectivity from this data is the computation of diffusion tractograms. In this paper, we present a novel and effective method for visualizing probabilistic tractograms within their anatomical context. Our illustrative rendering technique, called fiber stippling, is inspired by visualization standards as found in anatomical textbooks. These illustrations typically show slice-based projections of fiber pathways and are typically hand-drawn. Applying the automatized technique to diffusion tractography, we demonstrate its expressiveness and intuitive usability as well as a more objective way to present white-matter structure in the human brain.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"22 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":"134099341","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: 20

Visualizing virus population variability from next generation sequencing data 从下一代测序数据可视化病毒种群变异性

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BIOVIS.2011.6094058

M. Correll, Subhadip Ghosh, D. O’Connor, Michael Gleicher

{"title":"Visualizing virus population variability from next generation sequencing data","authors":"M. Correll, Subhadip Ghosh, D. O’Connor, Michael Gleicher","doi":"10.1109/BIOVIS.2011.6094058","DOIUrl":"https://doi.org/10.1109/BIOVIS.2011.6094058","url":null,"abstract":"Advances in genomic sequencing techniques allow for larger scale generation and usage of sequence data. While these techniques afford new types of analysis, they also generate new concerns with regards to data quality and data scale. We present a tool designed to assist in the exploration of the genetic variability of the population of viruses at multiple time points and in multiple individuals, a task that necessitates considering large amounts of sequence data and the quality issues inherent in obtaining such data in a practical manner. Our design affords the examination of the amount of variability and mutation at each position in the genome for many populations of viruses. Our design contains novel visualization techniques that support this specific class of analysis while addressing the issues of data aggregation, confidence visualization, and interaction support that arise when making use of large amounts of sequence data with variable uncertainty. These techniques generalize to a wide class of visualization problems where confidence is not known a priori, and aggregation in multiple directions is necessary.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"4 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":"125619885","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: 13

A visual analysis system for metabolomics data 代谢组学数据可视化分析系统

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BIOVIS.2011.6094050

Philip Livengood, Ross Maciejewski, Wei Chen, D. Ebert

引用次数: 6

Quick2Insight: A user-friendly framework for interactive rendering of biological image volumes Quick2Insight:一个用户友好的框架，用于生物图像卷的交互式渲染

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BioVis.2011.6094041

Yanling Liu, C. Lisle, Jack R. Collins

{"title":"Quick2Insight: A user-friendly framework for interactive rendering of biological image volumes","authors":"Yanling Liu, C. Lisle, Jack R. Collins","doi":"10.1109/BioVis.2011.6094041","DOIUrl":"https://doi.org/10.1109/BioVis.2011.6094041","url":null,"abstract":"This paper presents a new framework for simple, interactive volume exploration of biological datasets. We accomplish this by automatically creating dataset-specific transfer functions and utilizing them during direct volume rendering. The proposed method employs a K-Means++ clustering algorithm to classify a two-dimensional histogram created from the input volume. The classification process utilizes spatial and data properties from the volume. Then using properties derived from the classified clusters, our method automatically generates color and opacity transfer functions and presents the user with a high quality initial rendering of the volume data. Our method estimates classification parameters automatically, yet users are also allowed to input or override parameters to utilize pre-existing knowledge of their input data. User input is incorporated through the simple yet intuitive interface for transfer function manipulation included in our framework. Our new interface helps users focus on feature space exploration instead of the usual effort intensive, low-level widget manipulation. We evaluated the framework using three-dimensional medical and biological images. Our preliminary results demonstrate the effectiveness of our method of automating transfer function generation for high quality initial visualization. The proposed approach effectively generates automatic transfer functions and enables users to explore and interact with their data in an intuitive way, without requiring detailed knowledge of computer graphics or rendering techniques. Funded by NCI Contract No. HHSN261200800001E.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"3 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":"126616003","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

GenAMap: Visualization strategies for structured association mapping GenAMap:结构化关联映射的可视化策略

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BioVis.2011.6094052

Ross E. Curtis, Peter Kinnaird, E. Xing

{"title":"GenAMap: Visualization strategies for structured association mapping","authors":"Ross E. Curtis, Peter Kinnaird, E. Xing","doi":"10.1109/BioVis.2011.6094052","DOIUrl":"https://doi.org/10.1109/BioVis.2011.6094052","url":null,"abstract":"Association mapping studies promise to link DNA mutations to gene expression data, possibly leading to innovative treatments for diseases. One challenge in large-scale association mapping studies is exploring the results of the computational analysis to find relevant and interesting associations. Although many association mapping studies find associations from a genome-wide collection of genomic data to hundreds or thousands of traits, current visualization software only allow these associations to be explored one trait at a time. The inability to explore the association of a genomic location to multiple traits hides the inherent interaction between traits in the analysis. Additionally, researchers must rely on collections of in-house scripts and multiple tools to perform an analysis, adding time and effort to find interesting associations. In this paper, we present a novel visual analytics system called GenAMap. GenAMap replaces the time-consuming analysis of large-scale association mapping studies with exploratory visualization tools that give geneticists an overview of the data and lead them to relevant information. We present the results of a preliminary evaluation that validated our basic approach.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"12 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":"121226049","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: 13

TIALA — Time series alignment analysis 时间序列比对分析

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BIOVIS.2011.6094048

Günter Jäger, F. Battke, K. Nieselt

{"title":"TIALA — Time series alignment analysis","authors":"Günter Jäger, F. Battke, K. Nieselt","doi":"10.1109/BIOVIS.2011.6094048","DOIUrl":"https://doi.org/10.1109/BIOVIS.2011.6094048","url":null,"abstract":"The analysis of time series expression data is widely employed for investigating biological mechanisms. Microarrays are often used to generate time series for several different experimental conditions. These time series then need to be compared to each other. For a successful comparison it is necessary to perform a time series alignment because the experiments can differ in the number of time points, as well as in the time points themselves. In this work we propose a novel visual analytics approach for the analysis of multiple time series experiments in parallel. Our time series alignment analysis tool Tiala allows one to align multiple time series experiments and to visually explore the aligned expression profiles. A two- and three-dimensional visualization strategy was implemented that is especially designed to enhance the display of multiple aligned time series expression profiles. Tiala is available as a part of the microarray data analysis software Mayday. Mayday itself is open source software distributed under the terms of the GNU General Public License. It is available from http://www.microarray-analysis.org. We apply our approach to time series showing abiotic stress responses of Arabidopsis thaliana and to data sets from two replicates of the antibiotics producing bacterium Streptomyces coelicolor.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"41 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":"114671581","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

EVEVis: A multi-scale visualization system for dense evolutionary data EVEVis:用于密集进化数据的多尺度可视化系统

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BIOVIS.2011.6094059

Robert Miller, Vadim Mozhayskiy, I. Tagkopoulos, K. Ma

引用次数: 5

MDMap: A system for data-driven layout and exploration of molecular dynamics simulations MDMap:用于数据驱动布局和分子动力学模拟探索的系统

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BioVis.2011.6094055

Robert Patro, C. Y. Ip, Sujal Bista, D. Thirumalai, Samuel S. Cho, A. Varshney

{"title":"MDMap: A system for data-driven layout and exploration of molecular dynamics simulations","authors":"Robert Patro, C. Y. Ip, Sujal Bista, D. Thirumalai, Samuel S. Cho, A. Varshney","doi":"10.1109/BioVis.2011.6094055","DOIUrl":"https://doi.org/10.1109/BioVis.2011.6094055","url":null,"abstract":"Contemporary molecular dynamics simulations result in a glut of simulation data, making analysis and discovery a difficult and burdensome task. We present MDMap, a system designed to summarize long-running molecular dynamics (MD) simulations. We represent a molecular dynamics simulation as a state transition graph over a set of intermediate (stable and semi-stable) states. The transitions amongst the states together with their frequencies represent the flow of a biomolecule through the trajectory space. MDMap automatically determines potential intermediate conformations and the transitions amongst them by analyzing the conformational space explored by the MD simulation. MDMap is an automated system to visualize MD simulations as state-transition diagrams, and can replace the current tedious manual layouts of biomolecular folding landscapes with an automated tool. The layout of the representative states and the corresponding transitions among them is presented to the user as a visual synopsis of the long-running MD simulation. We compare and contrast multiple presentations of the state transition diagrams, such as conformational embedding, and spectral, hierarchical, and force-directed graph layouts. We believe this system could provide a road-map for the visualization of other stochastic time-varying simulations in a variety of different domains.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"61 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":"127658740","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: 11

Semantically steered visual analysis of highly detailed morphometric shape spaces 语义导向的高度详细的形态测量形状空间的视觉分析

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BioVis.2011.6094060

M. Hermann, A. C. Schunke, R. Klein

{"title":"Semantically steered visual analysis of highly detailed morphometric shape spaces","authors":"M. Hermann, A. C. Schunke, R. Klein","doi":"10.1109/BioVis.2011.6094060","DOIUrl":"https://doi.org/10.1109/BioVis.2011.6094060","url":null,"abstract":"A common technique in 3D shape analysis is to describe shape variability using a statistical deformation model (SDM). In contrast to the use of sparse landmark data for volume data this SDM is based on dense registrations of the input shapes. For a valuable exploration of the shape space in the setting of biological morphometrics we identified two prominent objectives for visual investigation. The first objective is to detect possible shape variations between anatomically different groups of individuals. The second is to integrate and exploit expert knowledge about relevant regions on the shapes. To meet the first objective, we advocate the use of dimensionality reduction methods combined with a parameterization defined on user specified classifications. This idea was already successfully applied in data-driven reflectance models and also turns out to be valuable in the context of biological morphometry, as it allows for intuitive exploration of shape variations. The second objective can be achieved by an appropriate weighted linear analysis which delivers a better approximation of shape variations in local neighbourhoods of a user defined region of interest. The methods were applied to real-world biological datasets of rodent mandibles and validated in cooperation with the MPI for Evolutionary Biology. For this purpose, we provide an interactive dynamic visualization of the shape space based on a custom GPU raycaster. A special feature of our implementation is that it builds the SDM directly on dense registrations of the volumes and does thereby not rely on a specific non-rigid registration method.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"7 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":"129037738","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: 15

Modeling and visualization of receptor clustering on the cellular membrane 细胞膜上受体聚集的建模和可视化

2011 IEEE Symposium on Biological Data Visualization (BioVis). Pub Date : 2011-10-23 DOI: 10.1109/BioVis.2011.6094042

M. Falk, M. Daub, G. Schneider, T. Ertl

{"title":"Modeling and visualization of receptor clustering on the cellular membrane","authors":"M. Falk, M. Daub, G. Schneider, T. Ertl","doi":"10.1109/BioVis.2011.6094042","DOIUrl":"https://doi.org/10.1109/BioVis.2011.6094042","url":null,"abstract":"In cell biology, apopotosis is a very important cellular process. Apopotosis, or programmed cell death, allows an organism to remove damaged or unneeded cells in a structured manner in contrast to necrosis. Ligands bind to the death receptors located on the cellular membrane forming ligand-receptor clusters. In this paper, we develop a novel mathematical model describing the stochastic process of the ligand-receptor clustering. To study the structure and the size of the ligand-receptor clusters, a stochastic particle simulation is employed. Besides the translation of the particles on the cellular membrane, we also take the particle rotation into account as we model binding sites explicitly. Glyph-based visualization techniques are used to validate and analyze the results of our in-silico model. Information on the individual clusters as well as particle-specific data can be selected by the user and is mapped to colors to highlight certain properties of the data. The results of our model look very promising. The visualization supports the process of model development by visual data analysis including the identification of cluster components as well as the illustration of particle trajectories.","PeriodicalId":354473,"journal":{"name":"2011 IEEE Symposium on Biological Data Visualization (BioVis).","volume":"7 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":"132248090","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: 8