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Visual Analytics for GCxGC-MS Data

By David Ebert1, Ross Maciejewski

1. Purdue University

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Abstract

Visual Analytics for OMIC Data

A critical issue for the CCE project is how to rapidly evaluate and validate model predictions. An interactive, integrated, visual and statistical analysis capability was developed that will serve as a model for future CCE projects. An interactive visual analytic approach harnesses the power of traditional analysis and data mining techniques, as well as the power of the human visual system for instantly detecting patterns, trends and clusters, and the increased performance of human reasoning through the use of external cognitive artifacts.

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Researchers should cite this work as follows:

  • David Ebert; Ross Maciejewski (2008), "Visual Analytics for GCxGC-MS Data," http://ccehub.org/resources/105.

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  1. biomarker discovery 13
  2. colorectal cancer 25
  3. OMIC analysis 27
  4. visual analytics 9

In This Series

  1. Syndromic Surveillance Hypothesis Development Using Visual Analytics

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    09 Sep 2008 | Downloads | Contributor(s): Ross Maciejewski, David Ebert

    When analyzing syndromic surveillance data, health care officials look for areas with unusually high cases of syndromes. Unfortunately, many outbreaks are difficult to detect because their signal is obscured by the statistical noise. Consequently, many detection algorithms have a high false …

  2. Visual Analytics for Cancer Care Engineering

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    29 Aug 2008 | Teaching Materials | Contributor(s): David Ebert

    The Purdue University Regional Visualization and Analytics Center (PURVAC) presents a visual analytics tool for analyzing GCxGC TOF Mass Spectrometry data for metabolomics samples.

  3. CCE Retreat 2008 Part III

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    28 Aug 2008 | Online Presentations | Contributor(s): Ann Christine Catlin, David Ebert

    Cancer Care Engineering Retreat Video Part III. (one hour) The following presentations are included in the video: Stan Hamilton, MD. Professor of Pathology. MD Anderson Cancer Care Center. (continued) Advances in Colorectal Cancer Biomarker Discovery. (00:00-7:35) David Ebert, …

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