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Homology-driven assembly of NOn-redundant protEin sequence sets (NOmESS) for mass spectrometry

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Temu,  Tikira
Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons78356

Mann,  Matthias
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Räschle,  Markus
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Cox,  Jürgen
Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society;

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Citation

Temu, T., Mann, M., Räschle, M., & Cox, J. (2016). Homology-driven assembly of NOn-redundant protEin sequence sets (NOmESS) for mass spectrometry. Bioinformatics, 32(9), 1417-1419. doi:10.1093/bioinformatics/btv756.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002A-E49A-1
Abstract
To enable mass spectrometry (MS)-based proteomic studies with poorly characterized organisms, we developed a computational workflow for the homology-driven assembly of a non-redundant reference sequence dataset. In the automated pipeline, translated DNA sequences (e.g. ESTs, RNA deep-sequencing data) are aligned to those of a closely related and fully sequenced organism. Representative sequences are derived from each cluster and joined, resulting in a non-redundant reference set representing the maximal available amino acid sequence information for each protein. We here applied NOmESS to assemble a reference database for the widely used model organism Xenopus laevis and demonstrate its use in proteomic applications.