Leveraging Genomics Software to Improve Proteomics Results

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Rigorous data analysis techniques are essential in quantifying the differential expression of proteins in biological samples of interest. Statistical methods from the microarray literature were applied to the analysis of two-dimensional difference gel electrophoresis (2-D DIGE) proteomics experiments, in the context of technical variability studies involving human plasma. Protein expression measurements were corrected to account for observed intensity-dependent biases within gels, and normalized to mitigate observed gel to gel variations. The methods improved upon the results achieved using the best currently available 2-D DIGE proteomics software. The spot-wise protein variance was reduced by 10% and the number of apparently differentially ... continued below

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PDF-file: 27 pages; size: 2.1 Mbytes

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Fodor, I K & Nelson, D O September 6, 2005.

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Rigorous data analysis techniques are essential in quantifying the differential expression of proteins in biological samples of interest. Statistical methods from the microarray literature were applied to the analysis of two-dimensional difference gel electrophoresis (2-D DIGE) proteomics experiments, in the context of technical variability studies involving human plasma. Protein expression measurements were corrected to account for observed intensity-dependent biases within gels, and normalized to mitigate observed gel to gel variations. The methods improved upon the results achieved using the best currently available 2-D DIGE proteomics software. The spot-wise protein variance was reduced by 10% and the number of apparently differentially expressed proteins was reduced by over 50%.

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PDF-file: 27 pages; size: 2.1 Mbytes

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  • Report No.: UCRL-TR-215176
  • Grant Number: W-7405-ENG-48
  • DOI: 10.2172/883739 | External Link
  • Office of Scientific & Technical Information Report Number: 883739
  • Archival Resource Key: ark:/67531/metadc891836

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Office of Scientific & Technical Information Technical Reports

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  • September 6, 2005

Added to The UNT Digital Library

  • Sept. 23, 2016, 2:42 p.m.

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  • Dec. 5, 2016, 11:03 p.m.

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Fodor, I K & Nelson, D O. Leveraging Genomics Software to Improve Proteomics Results, report, September 6, 2005; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc891836/: accessed August 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.