@inbook{9a061b6603714bbd8c5bd1782a1f7a62,
title = "Informatics and Statistics for Analyzing 2-D Gel Electrophoresis Images",
abstract = "Despite recent progress in “shotgun” peptide separation by integrated liquid chromatography and mass spectrometry (LC/MS), proteome coverage and reproducibility are still limited with this approach and obtaining enough replicate runs for biomarker discovery is a challenge. For these reasons, recent research demonstrates that there is a continuing need for protein separation by two-dimensional gel electrophoresis (2-DE). However, with traditional 2-DE informatics, the digitized images are reduced to symbolic data through spot detection and quantification before proteins are compared for differential expression by spot matching. Recently, a more robust and automated paradigm has emerged where gels are directly aligned in the image domain before spots are detected across the whole image set as a whole. In this chapter, we describe the methodology for both approaches and discuss the pitfalls present when reasoning statistically about the differential protein expression discovered.",
keywords = "2-D gel electrophoresis, Image alignment, Spot detection, Spot matching, Differential expression analysis, Clustering, DIGE",
author = "Andrew Dowsey and Morris, {J S} and Yang, {G Z} and Dunn, {M J}",
year = "2010",
doi = "10.1007/978-1-60761-444-9_16",
language = "English",
isbn = "9781607614432",
series = "Methods in Molecular Biology{\texttrademark}",
publisher = "Springer",
pages = "239--255",
editor = "Hubbard, {Simon J} and Jones, {Andrew R}",
booktitle = "Proteome Bioinformatics",
}