An iterative statistical approach to the identification of protein phosphorylation motifs from large-scale data sets

Nature Biotechnology

Volumn 23, Issue 11, 2005, Pages 1391-1398

  Schwartz, Daniel ^a   Gygi, Steven P ^a  

^a HARVARD MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENZYMES; ITERATIVE METHODS; SET THEORY;

DATA SETS; PHOSPHORYLATION;

PROTEINS;

SERINE; THREONINE; TYROSINE;

ALGORITHM; ARTICLE; MASS SPECTROMETRY; PRIORITY JOURNAL; PROTEIN DOMAIN; PROTEIN MOTIF; PROTEIN PHOSPHORYLATION; SEQUENCE ALIGNMENT; STATISTICAL ANALYSIS; VALIDATION PROCESS;

ALGORITHMS; AMINO ACID MOTIFS; BIOTECHNOLOGY; COMPUTATIONAL BIOLOGY; DATA INTERPRETATION, STATISTICAL; INTERNET; MASS SPECTROMETRY; MODELS, STATISTICAL; PEPTIDE MAPPING; PHOSPHORYLATION; PROGRAMMING LANGUAGES; PROTEINS; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE;

EID: 27944499451     PISSN: 10870156     EISSN: 15461696     Source Type: Journal    
DOI: 10.1038/nbt1146     Document Type: Article

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