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A hypergeometric probability model for protein identification and validation using tandem mass spectral data and protein sequence databases
Rovshan G. Sadygov
, John R. Yates
Research output
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Contribution to journal
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Article
›
peer-review
180
Scopus citations
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Dive into the research topics of 'A hypergeometric probability model for protein identification and validation using tandem mass spectral data and protein sequence databases'. Together they form a unique fingerprint.
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Keyphrases
Protein Database
100%
Protein Identification
100%
Mass Spectral Data
100%
Hypergeometric
100%
Protein Validation
100%
Tandem Mass
100%
Tandem Mass Spectra
100%
Probability Model
100%
Peptide Sequencing
28%
Fragment Ions
28%
Hypergeometric Distribution
28%
Hypergeometric Model
28%
Proteolytic Cleavage
14%
Digestion
14%
Protease
14%
Database Search
14%
False Positive Rate
14%
Database Search Algorithm
14%
Large Set
14%
Cleavage Specificity
14%
H-value
14%
Empirical Probability
14%
Spectrum Database
14%
Model Frequencies
14%
Sequence Match
14%
Weight Bias
14%
Database Size
14%
Probability-based Method
14%
Spectral Searching
14%
Engineering
Hypergeometric Distribution
100%
Search Algorithm
50%
Molecular Weight
50%
Fits and Tolerances
50%
Do Model
50%
Molecular Mass
50%