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Journal Article

An Iterative Strategy for Precursor Ion Selection for LC-MS/MS Based Shotgun Proteomics.

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Zerck,  Alexandra
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Nordhoff,  Eckhard
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

Mirgorodskaya,  Ekaterina
Max Planck Society;

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Lehrach,  Hans
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Gobom,  Johan
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Citation

Zerck, A., Nordhoff, E., Resemann, A., Mirgorodskaya, E., Suckau, D., Reinert, K., et al. (2009). An Iterative Strategy for Precursor Ion Selection for LC-MS/MS Based Shotgun Proteomics. Journal of Proteome Research, 8(7), 3239-3251. doi:10.1021/pr800835x.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0010-7DA5-5
Abstract
Currently, the precursor ion selection strategies in LC-MS mainly choose the most prominent peptide signals for MS/MS analysis. Consequently, high-abundance proteins are identified by MS/MS of many peptides, whereas proteins of lower abundance might elude identification. We present a novel, iterative and result-driven approach for precursor ion selection that significantly increases the efficiency of an MS/MS analysis by decreasing data redundancy and analysis time. By simulating different strategies for precursor ion selection on an existing data set, we compare our method to existing result-driven strategies and evaluate its performance with regard to mass accuracy, database size, and sample complexity.