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Protein sequence database search based on tandem mass spectrometry is an essential method for protein identification. As the computational demand increases, parallel computing has become an important...
Database searching is the technique of choice for shotgun proteomics, and to date much research effort has been spent on improving its effectiveness. However, database searching faces a serious challe...
De novo peptide sequencing has improved remarkably in the past decade as a result of better instruments and computational algorithms. However, de novo sequencing can correctly interpret only ∼3...
We present a new preprocessing method, PeakSelect, to improve the accuracy and efficiency of Tandem Mass-Spec peptide (protein) identification. The fundamental difference between noise and fragment i...
Peptide identification via tandem mass spectrometry is the basic task of current proteomics research. Due to the complexity of mass spectra, the majority of mass spectra cannot be interpreted at pres...
The assumption on the mass error distribution of fragment ions plays a crucial role in peptide identification by tandem mass spectra. Previous mass error models are the simplistic uniform or normal ...
To identify the unknown peptide sequences from the observed experimental MS/MS spectra, database searching is currently the most popular and reliable approach in high-throughput proteomics studies. We...
Shared Peak Count (SPC), i.e. the number of matched peaks between the experimental MS/MS spectrum and the theoretical one predicted from a peptide sequence in the database, is a widely used scoring me...
The correlation among fragment ions in a tandem mass spectrum is crucial in reducing stochastic mismatches for peptide identification by database searching. Until now, an efficient scoring algorithm ...

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