Statistics for proteomics: a review of tools for analyzing experimental data.

@article{Urfer2006StatisticsFP,
  title={Statistics for proteomics: a review of tools for analyzing experimental data.},
  author={Wolfgang Urfer and Marco Grzegorczyk and Klaus Jung},
  journal={Proteomics},
  year={2006},
  volume={6 Suppl 2},
  pages={
          48-55
        }
}
Most proteomics experiments make use of 'high throughput' technologies such as 2-DE, MS or protein arrays to measure simultaneously the expression levels of thousands of proteins. Such experiments yield large, high-dimensional data sets which usually reflect not only the biological but also technical and experimental factors. Statistical tools are essential for evaluating these data and preventing false conclusions. Here, an overview is given of some typical statistical tools for proteomics… CONTINUE READING
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