View Ovarian Cancer (NCI Q-Star Data) (public)

2011-09-07 12:21 by kidzik | Version 1 | Rating Empty StarEmpty StarEmpty StarEmpty StarEmpty StarEmpty Star
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Summary

The goal of this experiment is to identify proteomic patterns in serum that distinguish ovarian cancer from non-cancer.

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unknown (from UCI repository)
Dependencies
Tags
cancer Classification nci ovarian qstar
Attribute Types
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Original Data Format
arff
Name
Version mldata
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Names
Data (first 10 data points)
    Format not HDF5, zip or tar archive. Will parse the following text: @relation 'ovarian' @attribute A699C991 numeric @attribute A700C003 numeric @attribute A700C015 numeric @attribute A700C026 numeric @attribute A700C038 numeric @attribute A700C050 numeric @attribute A700C062 numeric @attribute A700C073 numeric @attribute A700C085 numeric
Description

The goal of this experiment is to identify proteomic patterns in serum that distinguish ovarian cancer from non-cancer. This study is significant to women who have a high risk of ovarian cancer due to family or personal history of cancer. Compared with PBSII proteomic data, the data obtained from ABI Hybrid Pulsar QqTOF instrument (Q-Star) were generated from a higher resolution mass spectrometer. The data provided here contains 216 samples, 121 cancer samples and 95 normal samples. The number of attributes is as many as 373,401. Thus, we have to split data into 10 files, each of them has around 37340 attributes.

URLs
http://datam.i2r.a-star.edu.sg/datasets/krbd/OvarianCancer/OvarianCancer-NCI-QStar.html
Publications
    Data Source
    http://datam.i2r.a-star.edu.sg/datasets/krbd/OvarianCancer/OvarianCancer-NCI-QStar.html
    Measurement Details
    Usage Scenario
    revision 1
    by kidzik on 2011-09-07 12:21

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    Acknowledgements

    This project is supported by PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning)
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