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Automated data integration and determination of posttranslational modifications with the protein inference engine.
MedLine Citation:
PMID:  21082440     Owner:  NLM     Status:  In-Process    
Abstract/OtherAbstract:
This chapter describes using the Protein Inference Engine (PIE) to integrate various types of data--especially top down and bottom up mass spectrometer (MS) data--to describe a protein's posttranslational modifications (PTMs). PTMs include cleavage events such as the n-terminal loss of methionine and residue modifications like phosphorylation. Modifications are key elements in many biological processes, but are difficult to study as no single, general method adequately characterizes a protein's PTMs; manually integrating data from several MS experiments is usually required. The PIE is designed to automate this process using a guess and refine process similar to how an expert manually integrates data. The PIE repeatedly "imagines" a possible modification set, evaluates it using available data, and then tries to improve on it. After many rounds of refinement, the resulting modification set is proposed as a candidate answer. Multiple candidate answers are generated to obtain both best and near-best answers. Near-best answers are crucial in allowing for proteins with more than one supported modification pattern (isoforms) and obtaining robust results given incomplete and inconsistent data.The goal of this chapter is to walk the reader through installing and using the downloadable version of PIE, both in general and by means of a specific, detailed example. The example integrates several types of experimental and background (prior) data. It is not a "perfect-world" scenario, but has been designed to illustrate several real-world difficulties that may be encountered when trying to analyze imperfect data.
Authors:
Stuart R Jefferys; Morgan C Giddings
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Methods in molecular biology (Clifton, N.J.)     Volume:  694     ISSN:  1940-6029     ISO Abbreviation:  Methods Mol. Biol.     Publication Date:  2011  
Date Detail:
Created Date:  2010-11-18     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9214969     Medline TA:  Methods Mol Biol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  255-90     Citation Subset:  IM    
Affiliation:
Department of Bioinformatics & Computational Biology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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