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Application of the data mining techniques to the systems biology of neuritogenesis

OPTIMIZATION METHODS & SOFTWARE 2007年第1期22卷 215-224页

作者： Zhang, Z. Q. Kammerdiner, A. R. Busygin, S. Ottens, A. K. Larner, S. F. Kobeissy, F. H. Pardalos, P. M. Hayes, R. L. Wang, K. K. Univ Florida Ctr Appl Optimizat Ind Gainesville FL USA Univ Florida Dept Syst & Ind Engn Gainesville FL USA Univ Florida Ctr Neuroproteom & Biomarkers Res Gainesville FL USA Univ Florida Ctr Traumat Brain Injury Studies Gainesville FL USA Univ Florida Dept Neurosci McKnight Brain Inst Gainesville FL 32610 USA Univ Florida Dept Psychiat McKnight Brain Inst Gainesville FL 32611 USA

A recent breakthrough in application of experimental methods to biomedicine not only has already resulted in accumulation of massive amounts of data, but also created new challenges in the field of data mining. This paper addresses the issue by combining advanced data mining techniques with the novel application of systems biology t o study axonal regeneration and neurogenesis. To obtain the data for analysis, a series of biological experiments are conducted, in which the rat pheochromocytoma cell PC-12 was used as an appropriate model for neuronal differentiation. The resulting DNA microarray data set is studied using a combination of methods - a statistical procedure for feature selection together with a dimensionality reduction technique. First, we apply feature selection, which can be based either on the Wilcoxon rank-sum test, or on the two-sample t-test, depending on the statistical properties of the data. Next, we utilized an efficient dimensionality reduction procedure called correspondence analysis to obtain a two-dimensional projection of the data, which allows us to perform a visual exploration of the patterns as well as to select the features corresponding to the top down-regulated and up-regulated genes.

关键词： data mining systems biology neurogenesis correspondence analysis feature selection

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visual analysis of gel-free Proteome data

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2006年第4期12卷 497-508页

作者： Linsen, L Löcherbach, J Berth, M Becher, D Bernhardt, J Ernst Moritz Arndt Univ Greifswald Dept Math & Comp Sci Greifswald Germany Ernst Moritz Arndt Univ Greifswald Dept Microbiol Greifswald Germany

We present a visual exploration system supporting protein analysis when using gel-free data acquisition methods. The data to be analyzed is obtained by coupling liquid chromatography (LC) with mass spectrometry ( MS). LC-MS data have the properties of being nonequidistantly distributed in the time dimension ( measured by LC) and being scattered in the mass-to-charge ratio dimension ( measured by MS). We describe a hierarchical data representation and visualization method for large LC-MS data. Based on this visualization, we have developed a tool that supports various data analysis steps. Our visual tool provides a global understanding of the data, intuitive detection and classification of experimental errors, and extensions to LC-MS/MS, LC/LC-MS, and LC/LC-MS/MS data analysis. Due to the presence of randomly occurring rare isotopes within the same protein molecule, several intensity peaks may be detected that all refer to the same peptide. We have developed methods to unite such intensity peaks. This deisotoping step is visually documented by our system, such that misclassification can be detected intuitively. For differential protein expression analysis, we compute and visualize the differences in protein amounts between experiments. In order to compute the differential expression, the experimental data need to be registered. For registration, we perform a nonrigid warping step based on landmarks. The landmarks can be assigned automatically using protein identification methods. We evaluate our methods by comparing protein analysis with and without our interactive visualization-based exploration tool.

关键词： interactive visual exploration hierarchical data representation visualization in bioinformatics proteomics

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An atmospheric visual analysis and exploration system

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2006年第5期12卷 1157-1164页

作者： Song, Yuyan Ye, Jing Svakhine, Nikolai Lasher-Trapp, Sonia Baldwin, Mike Ebert, David S. Purdue Univ W Lafayette IN 47907 USA

Meteorological research involves the analysis of multi-field, multi-scale, and multi-source data sets. In order to better understand these data sets, models and measurements at different resolutions must be analyzed. Unfortunately, traditional atmospheric visualization systems only provide tools to view a limited number of variables and small segments of the data. These tools are often restricted to two-dimensional contour or vector plots or three-dimensional isosurfaces. The meteorologist must mentally synthesize the data from multiple plots to glean the information needed to produce a coherent picture of the weather phenomenon of interest. In order to provide better tools to meteorologists and reduce system limitations, we have designed an integrated atmospheric visual analysis and exploration system for interactive analysis of weather data sets. Our system allows for the integrated visualization of 1D, 2D, and 3D atmospheric data sets in common meteorological grid structures and utilizes a variety of rendering techniques. These tools provide meteorologists with new abilities to analyze their data and answer questions on regions of interest, ranging from physics-based atmospheric rendering to illustrative rendering containing particles and glyphs. In this paper, we will discuss the use and performance of our visual analysis for two important meteorological applications. The first application is warm rain formation in small cumulus clouds. Here, our three-dimensional, interactive visualization of modeled drop trajectories within spatially correlated fields from a cloud simulation has provided researchers with new insight. Our second application is improving and validating severe storm models, specifically the Weather Research and Forecasting (WRF) model. This is done through correlative visualization of WRF model and experimental Doppler storm data.

关键词： weather visualization grid structures transfer function volume rendering volume visualization glyph rendering warm rain entrainment process

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Playing with maps - Explore, discover, learn, categorize, model, analyse, explain, present geographic and non-geographic data

Playing with maps - Explore, discover, learn, categorize, mo...

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10th International conference on Information visualization (IV06)

作者： Kraak, Menno-Jan ITC Dept Geoinformat Proc Enschede Netherlands

ISBN: (纸本)0769526020

Maps are especially known for their capability to provide insight in geographic patterns and trends. Maps do this well because they only present a selection of the complex reality and visualize it in an abstract way. But today they have many more roles to play. They should also be seen as flexible interface to geospatial data, since they offer interaction with the data behind the visual representation and additionally maps are instruments that encourage exploration. As such they are used to stimulate (visual) thinking about geospatial patterns, relationships, and trends. The context where maps like this operate is the world of Geovisualization which can be described as a loosely bounded domain that addresses the visual exploration, analysis, synthesis and presentation of geospatial data by integrating approaches from disciplines including cartography with those from scientific visualization, image analysis, information visualization, exploratory data analysis, visual analytics, and GIScience. Contact with all those disciplines has enriched the world of maps but have also stimulated others to use the map (metaphor) to visualize nongeographic data. The discussion will illustrated the new and exiting role maps can play to visualize geographic and non-geographic data in combination with other visual means.

关键词： Maps

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Pixnostics: Towards measuring the value of visualization

Pixnostics: Towards measuring the value of visualization

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IEEE Symposium on visual Analytics Science and Technology

作者： Schneidewind, Joern Sips, Mike Keim, Daniel A. Univ Konstanz D-7750 Constance Germany Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)1424405912

During the last two decades a wide variety of advanced methods for the visual exploration of large data sets have been proposed. For most of these techniques user interaction has become a crucial element, since there are many situations in which an user or an analyst has to select the right parameter settings from among many or select a subset of the available attribute space for the visualization process, in order to construct valuable visualizations that provide insight into the data and reveal interesting patterns. The right choice of input parameters is often essential, since suboptimal parameter settings or the investigation of irrelevant data dimensions make the exploration process more time consuming and may result in wrong conclusions. In this paper we propose a novel method for automatically determining meaningful parameter- and attribute settings based on the Information content of the resulting visualizations. Our technique called Pixnostics, in analogy to Scagnostics[1] automatically analyses pixel images resulting from diverse parameter mappings and ranks them according to the potential value for the user. This allows a more effective and more efficient visual data analysis process, since the attribute/parameter space is reduced to meaningful selections and thus the analyst obtains faster insight into the data. Real world applications are provided to show the benefit of the proposed approach.

关键词： visual data exploration visualization technique visual Analytics

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visual analysis of gel-free Proteome data

Visual analysis of gel-free Proteome data

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IEEE visualization 2005 conference

关键词： interactive visual exploration hierarchical data representation visualization in bioinformatics proteomics

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SoC design space exploration through automated IP selection from SystemC IP library

SoC design space exploration through automated IP selection ...

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IEEE International SOC conference

作者： Mathaikutty, Deepak Shukla, Sandeep Virginia Polytech Inst & State Univ CESCA Blacksburg VA 24061 USA

ISBN: (纸本)0780397819

Given a SystemC IP library, constructing SoC simulation models for design space exploration often distract Oesigners from system architecture concerns to software engineering and proyamming concerns. Fast design space exploration using a visual architectural specification framework followed by automated IP selection and construction of simulation models without having to programmatically composing the IPs is the main attractive feature of the component composition framework developed and described in this paper. We employ concepts metamodeling for the visual specification, meta-data for kes IPopf reflection, and algorithn-dc analysis of metadata for IP-selection, matching and executable model construction.

关键词： Microprocessor chips

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SRS browser:: A visual interface to the sequence retrieval system

SRS browser:: A visual interface to the sequence retrieval s...

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conference on visualization and data analysis 2006

作者： Mane, Ketan K. Borner, Katy Indiana Univ Sch Lib & Informat Sci 10th St & Jordan Ave Bloomington IN 47405 USA

ISBN: (纸本)0819461008

This paper presents a novel approach to the visual exploration and navigation of complex association networks of biological data sets. e.g., published papers, gene or protein information. The generic approach was implemented in the SRS Browser as an alternative visual interface to the highly used Sequence Retrieval System (SRS) [1]. SRS Supports keyword-based search of about 400 biomedical databases. While the SRS presents search results as rank-ordered lists of matching entities, the SRS Browser displays entities and their relations for interactive exploration. A formal usability study was conducted to examine the SRS Browser interface's capabilities to Support knowledge discovery and management.

关键词： information visualization visual interfaces to digital libraries Sequence Retrieval System SRS

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Evaluating visual table data understanding

Evaluating visual table data understanding

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BELIV'06: BEyond time and errors - novel EvaLuation methods for Information visualization. A workshop of the AVI 2006 International Working conference

作者： Henry, Nathalie Fekete, Jean-Daniel INRIA Futurs LRI Univ. Paris-Sud 91405 Orsay France

ISBN: (纸本)1595935622

In this paper, we focus on evaluating how information visualization supports exploration for visual table data. We present a controlled experiment designed to evaluate how the layout of table data affects the user understanding and his exploration process. This experiment raised interesting problems from the design phase to the data analysis. We present our task taxonomy, the experiment procedure and give clues about data collection and analysis. We conclude with lessons learnt from this experiment and discuss the format of future evaluation. Copyright 2006 ACM.

关键词： Information analysis

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visualization and analysis of large data collections: a case study applied to confocal microscopy data

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2006年第5期12卷 1251-1258页

作者： de Leeuw, Wim Verschure, Pernette J. van Liere, Robert CWI Ctr Math & Comp Sci NL-1009 AB Amsterdam Netherlands

In this paper we propose an approach in which interactive visualization and analysis are combined with batch tools for the processing of large data collections. Large and heterogeneous data collections are difficult to analyze and pose specific problems to interactive visualization. Application of the traditional interactive processing and visualization approaches as well as batch processing encounter considerable drawbacks for such large and heterogeneous data collections due to the amount and type of data. Computing resources are not sufficient for interactive exploration of the data and automated analysis has the disadvantage that the user has only limited control and feedback on the analysis process. In our approach, an analysis procedure with features and attributes of interest for the analysis is defined interactively. This procedure is used for off-line processing of large collections of data sets. The results of the batch process along with "visual summaries" are used for further analysis. visualization is not only used for the presentation of the result, but also as a tool to monitor the validity and quality of the operations performed during the batch process. Operations such as feature extraction and attribute calculation of the collected data sets are validated by visual inspection. This approach is illustrated by an extensive case study, in which a collection of confocal microscopy data sets is analyzed.

关键词： biomedical visualization features in volume data sets large data set visualization

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