Literature DB >> 18283661

The myth of automated, high-throughput two-dimensional gel analysis.

Brittan N Clark1, Howard B Gutstein.   

Abstract

Many software packages have been developed to process and analyze 2-D gel images. Some programs have been touted as automated, high-throughput solutions. We tested five commercially available programs using 18 replicate gels of a rat brain protein extract. We determined computer processing time, approximate spot editing time, time required to correct spot mismatches, as well as total processing time. We also determined the number of spots automatically detected, number of spots kept after manual editing, and the percentage of automatically generated correct matches. We also determined the effect of increasing the number of replicate gels on spot matching efficiency for two of the programs. We found that for all programs tested, less than 3% of the total processing time was automated. The remainder of the time was spent in manual, subjective editing of detected spots and computer generated matches. Total processing time for 18 gels varied from 22 to 84 h. The percentage of correct matches generated automatically varied from 1 to 62%. Increasing the number of gels in an experiment dramatically reduced the percentage of automatically generated correct matches. Our results demonstrate that these 2-D gel analysis programs are not automatic or rapid, and also suggest that matching accuracy decreases as experiment size increases.

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Year:  2008        PMID: 18283661     DOI: 10.1002/pmic.200700709

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


  11 in total

1.  AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA.

Authors:  Jeffrey S Morris; Veerabhadran Baladandayuthapani; Richard C Herrick; Pietro Sanna; Howard Gutstein
Journal:  Ann Appl Stat       Date:  2011-01-01       Impact factor: 2.083

2.  Detection and Quantification of Protein Spots by Pinnacle.

Authors:  Jeffrey S Morris; Howard B Gutstein
Journal:  Methods Mol Biol       Date:  2016

Review 3.  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

4.  Informatics and statistics for analyzing 2-d gel electrophoresis images.

Authors:  Andrew W Dowsey; Jeffrey S Morris; Howard B Gutstein; Guang-Zhong Yang
Journal:  Methods Mol Biol       Date:  2010

5.  Statistical Contributions to Bioinformatics: Design, Modeling, Structure Learning, and Integration.

Authors:  Jeffrey S Morris; Veerabhadran Baladandayuthapani
Journal:  Stat Modelling       Date:  2017-06-15       Impact factor: 2.039

6.  Highlights on the capacities of "Gel-based" proteomics.

Authors:  François Chevalier
Journal:  Proteome Sci       Date:  2010-04-28       Impact factor: 2.480

7.  Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches.

Authors:  Jeffrey S Morris
Journal:  Stat Interface       Date:  2012-01-01       Impact factor: 0.582

8.  Evaluating the performance of new approaches to spot quantification and differential expression in 2-dimensional gel electrophoresis studies.

Authors:  Jeffrey S Morris; Brittan N Clark; Wei Wei; Howard B Gutstein
Journal:  J Proteome Res       Date:  2010-01       Impact factor: 4.466

9.  Two-Dimensional Gel Electrophoresis Image Analysis.

Authors:  Elisa Robotti; Elisa Calà; Emilio Marengo
Journal:  Methods Mol Biol       Date:  2021

10.  A novel Gaussian extrapolation approach for 2D gel electrophoresis saturated protein spots.

Authors:  Massimo Natale; Alfonso Caiazzo; Enrico M Bucci; Elisa Ficarra
Journal:  Genomics Proteomics Bioinformatics       Date:  2012-11-07       Impact factor: 7.691

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