Two-Dimensional Gel Electrophoresis Image Analysis via Dedicated Software Packages

  • Martin H. MaurerEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1384)


Analyzing two-dimensional gel electrophoretic images is supported by a number of freely and commercially available software. Although the respective program is highly specific, all the programs follow certain standardized algorithms. General steps are: (1) detecting and separating individual spots, (2) subtracting background, (3) creating a reference gel and (4) matching the spots to the reference gel, (5) modifying the reference gel, (6) normalizing the gel measurements for comparison, (7) calibrating for isoelectric point and molecular weight markers, and moreover, (8) constructing a database containing the measurement results and (9) comparing data by statistical and bioinformatic methods.

Key words

Proteomics Two-dimensional gel electrophoresis 2-D GE Bioinformatics Image analysis 2-D software 




2-D GE

Two-dimensional gel electrophoresis


Analysis of variance


Mass spectrometry


Molecular weight


Optical density


Tagged image file format



The author has been supported by grants of the European Union within the Framework Programme 7, the German Ministry of Research and Education (BMBF) within the National Genome Research Network (NGFN-2), the German Research Foundation DFG, the intramural program of the Medical Faculty of the University of Heidelberg, the Steuben-Schurz Society, and the Estate of Friedrich Fischer. The author thanks Professor em. Dr. Wolfgang Kuschinsky, Heidelberg, for his sustained support and dedicates this work to his 70th birthday.


  1. 1.
    Maurer MH, Kuschinsky W (2007) Proteomics. In: Lajtha A (ed) Handbook of neurochemistry and molecular neurobiology, 3rd edn. Springer, New York, pp 737–769CrossRefGoogle Scholar
  2. 2.
    Berth M, Moser FM, Kolbe M et al. (2007) The state of the art in the analysis of two-dimensional gel electrophoresis images. Appl Microbiol Biotechnol 76:1223–1243PubMedCentralCrossRefPubMedGoogle Scholar
  3. 3.
    Maurer MH (2006) Software analysis of two-dimensional electrophoretic gels in proteomic experiments. Curr Bioinformatics 1:255–262CrossRefGoogle Scholar
  4. 4.
    Pleissner KP, Hoffmann F, Kriegel K et al. (1999) New algorithmic approaches to protein spot detection and pattern matching in two-dimensional electrophoresis gel databases. Electrophoresis 20:755–765CrossRefPubMedGoogle Scholar
  5. 5.
    Lemkin PF (1999) Comparing 2-D electrophoretic gels across Internet databases. Methods Mol Biol 112:393–410PubMedGoogle Scholar
  6. 6.
    Oye OK, Jorgensen KM, Hjelle SM et al. (2013) Gel2DE—a software tool for correlation analysis of 2D gel electrophoresis data. BMC Bioinformatics 14:215PubMedCentralCrossRefPubMedGoogle Scholar
  7. 7.
    Natale M, Maresca B, Abrescia P et al. (2011) Image analysis workflow for 2-D electrophoresis gels based on ImageJ. Proteomics Insights 4:37–49Google Scholar
  8. 8.
    Morris JS, Clark BN, Gutstein HB (2008) Pinnacle: a fast, automatic and accurate method for detecting and quantifying protein spots in 2-dimensional gel electrophoresis data. Bioinformatics 24:529–536PubMedCentralCrossRefPubMedGoogle Scholar
  9. 9.
    Li F, Seillier-Moiseiwitsch F (2011) RegStatGel: proteomic software for identifying differentially expressed proteins based on 2D gel images. Bioinformation 6:389–390PubMedCentralCrossRefPubMedGoogle Scholar
  10. 10.
    Maurer MH (2012) Two-dimensional protein analysis of neural stem cells. In: Karamanis Y (ed) Expression profiling in neuroscience. Humana Press, Totowa, NJ, pp 101–117CrossRefGoogle Scholar
  11. 11.
    Adobe Systems Incorporated (1992) TIFF Revision 6.0. Accessed 2013-12-18.
  12. 12.
    Maurer MH, Feldmann RE Jr, Brömme JO et al. (2005) Comparison of statistical approaches for the analysis of proteome expression data of differentiating neural stem cells. J Proteome Res 4:96–100CrossRefPubMedGoogle Scholar
  13. 13.
    Maurer MH (2005) Comparison of large proteomic datasets. Curr Proteomics 2:179–189CrossRefGoogle Scholar
  14. 14.
    Maurer MH (2004) The path to enlightenment: making sense of genomic and proteomic information. Genomics Proteomics Bioinformatics 2:123–131PubMedGoogle Scholar
  15. 15.
    Chakravarti DN, Chakravarti B, Moutsatsos I (2002) Informatic tools for proteome profiling. Biotechniques Suppl 4–10:12–15Google Scholar
  16. 16.
    Kanehisa M, Bork P (2003) Bioinformatics in the post-sequence era. Nat Genet 33(Suppl):305–310CrossRefPubMedGoogle Scholar
  17. 17.
    Boguski MS, McIntosh MW (2003) Biomedical informatics for proteomics. Nature 422:233–237CrossRefPubMedGoogle Scholar
  18. 18.
    Maurer MH (2012) Web-based tools for the interpretation of chain-like protein spot patterns. Curr Proteomics 9:18–25CrossRefGoogle Scholar
  19. 19.
    Bettens E, Scheunders P, Van Dyck D et al. (1997) Computer analysis of two-dimensional electrophoresis gels: a new segmentation and modeling algorithm. Electrophoresis 18:792–798CrossRefPubMedGoogle Scholar
  20. 20.
    Maurer MH (2004) Simple method for three-dimensional representation of 2-DE spots using a spreadsheet program. J Proteome Res 3:665–666CrossRefPubMedGoogle Scholar
  21. 21.
    Seillier-Moiseiwitsch F, Trost DC, Moiseiwitsch J (2002) Statistical methods for proteomics. Methods Mol Biol 184:51–80PubMedGoogle Scholar
  22. 22.
    Appel RD, Vargas JR, Palagi PM et al. (1997) Melanie II–a third-generation software package for analysis of two- dimensional electrophoresis images: II. Algorithms. Electrophoresis 18:2735–2748CrossRefPubMedGoogle Scholar
  23. 23.
    Dowsey AW, Dunn MJ, Yang GZ (2003) The role of bioinformatics in two-dimensional gel electrophoresis. Proteomics 3:1567–1596CrossRefPubMedGoogle Scholar
  24. 24.
    Mahon P, Dupree P (2001) Quantitative and reproducible two-dimensional gel analysis using Phoretix 2D Full. Electrophoresis 22:2075–2085CrossRefPubMedGoogle Scholar
  25. 25.
    Appel RD, Bairoch A, Sanchez JC et al. (1996) Federated two-dimensional electrophoresis database: a simple means of publishing two-dimensional electrophoresis data. Electrophoresis 17:540–546CrossRefPubMedGoogle Scholar
  26. 26.
    Mostaguir K, Hoogland C, Binz PA et al. (2003) The Make 2D-DB II package: conversion of federated two-dimensional gel electrophoresis databases into a relational format and interconnection of distributed databases. Proteomics 3:1441–1444CrossRefPubMedGoogle Scholar
  27. 27.
    Vizcaino JA, Reisinger F, Cote R et al. (2011) PRIDE and “Database on Demand” as valuable tools for computational proteomics. Methods Mol Biol 696:93–105CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Physiology and PathophysiologyUniversity of HeidelbergHeidelbergGermany
  2. 2.Mariaberg Hospital for Child and Adolescent PsychiatryGammertingen-MariabergGermany

Personalised recommendations