Literature DB >> 15378705

Statistical exploration of variation in quantitative two-dimensional gel electrophoresis data.

John S Gustafsson1, Robert Ceasar, Chris A Glasbey, Anders Blomberg, Mats Rudemo.   

Abstract

Two-dimensional gel electrophoresis is a major technique in global analysis at the protein level. This paper presents an examination of spot volume data from three gel sets with radioactively labeled yeast Saccharomyces cerevisiae proteins. A strong variance versus mean dependence in data was found to be stabilized by applying a shifted logarithmic transformation. However, transformed data showed a remaining substantial variance heterogeneity for different proteins. Furthermore, examination of studentized residuals revealed that transformed data were approximately normally distributed and that there were spatial correlations among the measurement errors in the gel.

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Year:  2004        PMID: 15378705     DOI: 10.1002/pmic.200300824

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  5 in total

Review 1.  Image analysis tools and emerging algorithms for expression proteomics.

Authors:  Andrew W Dowsey; Jane A English; Frederique Lisacek; Jeffrey S Morris; Guang-Zhong Yang; Michael J Dunn
Journal:  Proteomics       Date:  2010-12       Impact factor: 3.984

2.  Proteomic analyses of the Xiphophorus Gordon-Kosswig melanoma model.

Authors:  Amy N Perez; Lee Oehlers; Shelia J Heater; Rachell E Booth; Ronald B Walter; Wendi M David
Journal:  Comp Biochem Physiol C Toxicol Pharmacol       Date:  2011-06-06       Impact factor: 3.228

3.  Urine collected from diapers can be used for 2-D PAGE in infants and young children.

Authors:  Mary Jayne Kennedy; Angela Griffin; Ruifeng Su; Michael Merchant; Jon Klein
Journal:  Proteomics Clin Appl       Date:  2009-08       Impact factor: 3.494

4.  Normalization and expression changes in predefined sets of proteins using 2D gel electrophoresis: a proteomic study of L-DOPA induced dyskinesia in an animal model of Parkinson's disease using DIGE.

Authors:  Kim Kultima; Birger Scholz; Henrik Alm; Karl Sköld; Marcus Svensson; Alan R Crossman; Erwan Bezard; Per E Andrén; Ingrid Lönnstedt
Journal:  BMC Bioinformatics       Date:  2006-10-26       Impact factor: 3.169

5.  A probabilistic framework for peptide and protein quantification from data-dependent and data-independent LC-MS proteomics experiments.

Authors:  Keith Richardson; Richard Denny; Chris Hughes; John Skilling; Jacek Sikora; Michał Dadlez; Angel Manteca; Hye Ryung Jung; Ole Nørregaard Jensen; Virginie Redeker; Ronald Melki; James I Langridge; Johannes P C Vissers
Journal:  OMICS       Date:  2012-08-07
  5 in total

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