Bayesian proteoform modeling improves protein quantification of global proteomic measurements

Molecular and Cellular Proteomics

Volumn 13, Issue 12, 2014, Pages 3639-3646

  Webb Robertson, Bobbie Jo M ^a   Matzke, Melissa M ^a   Datta, Susmita ^b   Payne, Samuel H ^a   Kang, Jiyun ^a   Bramer, Lisa M ^a   Nicora, Carrie D ^a   Shukla, Anil K ^a   Metz, Thomas O ^a   Rodland, Karin D ^a   Smith, Richard D ^a   Tardiff, Mark F ^a   McDermott, Jason E ^a   Pounds, Joel G ^a   Waters, Katrina M ^a  

^a PACIFIC NORTHWEST NATIONAL LABORATORY   (United States)

^b UNIVERSITY OF LOUISVILLE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BAYES THEOREM; BAYESIAN PROTEOFORM QUANTIFICATION MODEL; BLOOD SAMPLING; MOUSE; NONHUMAN; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN EXPRESSION; PROTEIN FUNCTION; PROTEOMICS; ALTERNATIVE RNA SPLICING; AMINO ACID SEQUENCE; ANIMAL; COMPUTER PROGRAM; GENETICS; HUMAN; METABOLISM; MOLECULAR GENETICS; PROCEDURES; PROTEIN PROCESSING; STATISTICS AND NUMERICAL DATA;

PLASMA PROTEIN; PROTEOME;

ALTERNATIVE SPLICING; AMINO ACID SEQUENCE; ANIMALS; BAYES THEOREM; BLOOD PROTEINS; HUMANS; MICE; MOLECULAR SEQUENCE DATA; PROTEIN PROCESSING, POST-TRANSLATIONAL; PROTEOME; PROTEOMICS; SOFTWARE;

EID: 84909960219     PISSN: 15359476     EISSN: 15359484     Source Type: Journal    
DOI: 10.1074/mcp.o113.030932     Document Type: Article

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