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2-D PAGE Map Analysis

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Cover of '2-D PAGE Map Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Sources of Experimental Variation in 2-D Maps: The Importance of Experimental Design in Gel-Based Proteomics
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    Chapter 2 Decoding 2-D Maps by Autocovariance Function
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    Chapter 3 Two-Dimensional Gel Electrophoresis Image Analysis via Dedicated Software Packages
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    Chapter 4 Comparative Evaluation of Software Features and Performances
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    Chapter 5 Image Pretreatment Tools I: Algorithms for Map Denoising and Background Subtraction Methods
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    Chapter 6 Image Pretreatment Tools II: Normalization Techniques for 2-DE and 2-D DIGE
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    Chapter 7 Spot Matching of 2-DE Images Using Distance, Intensity, and Pattern Information
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    Chapter 8 Algorithms for Warping of 2-D PAGE Maps
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    Chapter 9 2-DE Gel Analysis: The Spot Detection
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    Chapter 10 2-D PAGE Map Analysis
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    Chapter 11 Detection and Quantification of Protein Spots by Pinnacle
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    Chapter 12 A Novel Gaussian Extrapolation Approach for 2-D Gel Electrophoresis Saturated Protein Spots
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    Chapter 13 Multiple Testing and Pattern Recognition in 2-DE Proteomics
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    Chapter 14 Chemometric Multivariate Tools for Candidate Biomarker Identification: LDA, PLS-DA, SIMCA, Ranking-PCA
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    Chapter 15 The Use of Legendre and Zernike Moment Functions for the Comparison of 2-D PAGE Maps
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    Chapter 16 Nonlinear Dimensionality Reduction by Minimum Curvilinearity for Unsupervised Discovery of Patterns in Multidimensional Proteomic Data
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    Chapter 17 Differential Analysis of 2-D Maps by Pixel-Based Approaches
Attention for Chapter 5: Image Pretreatment Tools I: Algorithms for Map Denoising and Background Subtraction Methods
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Chapter title
Image Pretreatment Tools I: Algorithms for Map Denoising and Background Subtraction Methods
Chapter number 5
Book title
2-D PAGE Map Analysis
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3255-9_5
Pubmed ID
Book ISBNs
978-1-4939-3254-2, 978-1-4939-3255-9
Authors

Carlo Vittorio Cannistraci, Massimo Alessio

Abstract

One of the critical steps in two-dimensional electrophoresis (2-DE) image pre-processing is the denoising, that might aggressively affect either spot detection or pixel-based methods. The Median Modified Wiener Filter (MMWF), a new nonlinear adaptive spatial filter, resulted to be a good denoising approach to use in practice with 2-DE. MMWF is suitable for global denoising, and contemporary for the removal of spikes and Gaussian noise, being its best setting invariant on the type of noise. The second critical step rises because of the fact that 2-DE gel images may contain high levels of background, generated by the laboratory experimental procedures, that must be subtracted for accurate measurements of the proteomic optical density signals. Here we discuss an efficient mathematical method for background estimation, that is suitable to work even before the 2-DE image spot detection, and it is based on the 3D mathematical morphology (3DMM) theory.

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Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Professor > Associate Professor 1 33%
Unknown 1 33%
Readers by discipline Count As %
Physics and Astronomy 1 33%
Engineering 1 33%
Unknown 1 33%