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The state of the art in the analysis of two-dimensional gel electrophoresis images.

Berth M, Moser FM, Kolbe M, Bernhardt J - Appl. Microbiol. Biotechnol. (2007)

Bottom Line: Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments.Challenges for analysis software as well as good practices are highlighted.We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

View Article: PubMed Central - PubMed

Affiliation: DECODON GmbH, Rathenau-Strasse 49a, 17489 Greifswald, Germany.

ABSTRACT
Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

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Related in: MedlinePlus

Decomposition of the raw image into background, noise, and cleaned images. Image filters can be used to determine background and noise, leaving the quantitative protein spot information in the cleaned image. a Raw image, b speckles and noise, c background, d cleaned image
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Fig6: Decomposition of the raw image into background, noise, and cleaned images. Image filters can be used to determine background and noise, leaving the quantitative protein spot information in the cleaned image. a Raw image, b speckles and noise, c background, d cleaned image

Mentions: Image warping leads to changed quantitative data, so quantitation should be done on the original images, or the warping should incorporate a factor for volume compensation (Dowsey et al. 2006) to minimize quantitative side effects. Several types of image filtering algorithms are used by 2-D gel image analysis software to remove background and noise (Fig. 6). These filters are applied within the software for correct quantitation and for optimizing the appearance of the image on the computer screen.Fig. 6


The state of the art in the analysis of two-dimensional gel electrophoresis images.

Berth M, Moser FM, Kolbe M, Bernhardt J - Appl. Microbiol. Biotechnol. (2007)

Decomposition of the raw image into background, noise, and cleaned images. Image filters can be used to determine background and noise, leaving the quantitative protein spot information in the cleaned image. a Raw image, b speckles and noise, c background, d cleaned image
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2279157&req=5

Fig6: Decomposition of the raw image into background, noise, and cleaned images. Image filters can be used to determine background and noise, leaving the quantitative protein spot information in the cleaned image. a Raw image, b speckles and noise, c background, d cleaned image
Mentions: Image warping leads to changed quantitative data, so quantitation should be done on the original images, or the warping should incorporate a factor for volume compensation (Dowsey et al. 2006) to minimize quantitative side effects. Several types of image filtering algorithms are used by 2-D gel image analysis software to remove background and noise (Fig. 6). These filters are applied within the software for correct quantitation and for optimizing the appearance of the image on the computer screen.Fig. 6

Bottom Line: Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments.Challenges for analysis software as well as good practices are highlighted.We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

View Article: PubMed Central - PubMed

Affiliation: DECODON GmbH, Rathenau-Strasse 49a, 17489 Greifswald, Germany.

ABSTRACT
Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

Show MeSH
Related in: MedlinePlus