Document Detail

Image analysis tools and emerging algorithms for expression proteomics.
MedLine Citation:
PMID:  21046614     Owner:  NLM     Status:  MEDLINE    
Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-DE technique of protein separation, and by first covering signal analysis for MS, we also explain the current image analysis workflow for the emerging high-throughput 'shotgun' proteomics platform of LC coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whereas existing commercial and academic packages and their workflows are described from both a user's and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models, and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS.
Andrew W Dowsey; Jane A English; Frederique Lisacek; Jeffrey S Morris; Guang-Zhong Yang; Michael J Dunn
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Review    
Journal Detail:
Title:  Proteomics     Volume:  10     ISSN:  1615-9861     ISO Abbreviation:  Proteomics     Publication Date:  2010 Dec 
Date Detail:
Created Date:  2010-11-26     Completed Date:  2011-02-25     Revised Date:  2014-09-12    
Medline Journal Info:
Nlm Unique ID:  101092707     Medline TA:  Proteomics     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  4226-57     Citation Subset:  IM    
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MeSH Terms
Chromatography, Liquid
Data Interpretation, Statistical
Electrophoresis, Gel, Two-Dimensional
Gene Expression*
Image Processing, Computer-Assisted / methods*
Mass Spectrometry
Proteome / analysis*
Signal Processing, Computer-Assisted
Grant Support
CA107304/CA/NCI NIH HHS; R01 CA107304/CA/NCI NIH HHS; R01 CA107304-05/CA/NCI NIH HHS; R01 CA107304-06/CA/NCI NIH HHS
Reg. No./Substance:
Erratum In:
Proteomics. 2011 Jun;11(11):2359

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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