Tandem mass spectrometry of human tryptic blood peptides calculated by a statistical algorithm and captured by a relational database with exploration by a general statistical analysis system
| Autor: | Ron Beavis, Peter Bowden, John Marshall |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Relational database
Protein Hydrolysates Biophysics Peptide Computational biology Mass spectrometry computer.software_genre Tandem mass spectrometry Biochemistry Goodness of fit Peptide mass fingerprinting Peptide Library Tandem Mass Spectrometry RefSeq Humans Databases Protein chemistry.chemical_classification Electronic Data Processing Blood Proteins Blood proteins Peptide Fragments chemistry Data Interpretation Statistical Tryptases Data mining computer Algorithms Software |
| Zdroj: | Journal of proteomics. 73(1) |
| ISSN: | 1876-7737 |
| Popis: | A goodness of fit test may be used to assign tandem mass spectra of peptides to amino acid sequences and to directly calculate the expected probability of mis-identification. The product of the peptide expectation values directly yields the probability that the parent protein has been mis-identified. A relational database could capture the mass spectral data, the best fit results, and permit subsequent calculations by a general statistical analysis system. The many files of the Hupo blood protein data correlated by X!TANDEM against the proteins of ENSEMBL were collected into a relational database. A redundant set of 247,077 proteins and peptides were correlated by X!TANDEM, and that was collapsed to a set of 34,956 peptides from 13,379 distinct proteins. About 6875 distinct proteins were only represented by a single distinct peptide, 2866 proteins showed 2 distinct peptides, and 3454 proteins showed at least three distinct peptides by X!TANDEM. More than 99% of the peptides were associated with proteins that had cumulative expectation values, i.e. probability of false positive identification, of one in one hundred or less. The distribution of peptides per protein from X!TANDEM was significantly different than those expected from random assignment of peptides. |
| Databáze: | OpenAIRE |
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