Large-Scale Discovery and Characterization of Protein Regulatory Motifs in Eukaryotes
Supporting Files
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Dec 29 2010
File Language:
English
Details
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Alternative Title:PLoS One
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Personal Author:
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Description:The increasing ability to generate large-scale, quantitative proteomic data has brought with it the challenge of analyzing such data to discover the sequence elements that underlie systems-level protein behavior. Here we show that short, linear protein motifs can be efficiently recovered from proteome-scale datasets such as sub-cellular localization, molecular function, half-life, and protein abundance data using an information theoretic approach. Using this approach, we have identified many known protein motifs, such as phosphorylation sites and localization signals, and discovered a large number of candidate elements. We estimate that ~80% of these are novel predictions in that they do not match a known motif in both sequence and biological context, suggesting that post-translational regulation of protein behavior is still largely unexplored. These predicted motifs, many of which display preferential association with specific biological pathways and non-random positioning in the linear protein sequence, provide focused hypotheses for experimental validation.
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Subjects:
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Source:PLoS One. 5(12).
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Pubmed ID:21206902
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Pubmed Central ID:PMC3012054
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Document Type:
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Funding:
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Volume:5
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Issue:12
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Collection(s):
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Main Document Checksum:urn:sha256:eed9872afa47e76a832c44f4629f3b319e72d140c9fa32566e176602b79a5d69
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Download URL:
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File Type:
Supporting Files
File Language:
English
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