The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
A Proteomics Search Algorithm Specifically Designed for High-Resolution Tandem Mass Spectra
Open accessAbstract
The acquisition of high-resolution tandem mass spectra (MS/MS) is becoming more prevalent in proteomics, but most researchers employ peptide identification algorithms that were designed prior to this development. Here, we demonstrate new software, Morpheus, designed specifically for high-mass accuracy data, based on a simple score that is little more than the number of matching products. For a diverse collection of data sets from a variety of organisms (E. coli, yeast, human) acquired on a variety of instruments (quadrupole-time-of-flight, ion trap-orbitrap, and quadrupole-orbitrap) in different laboratories, Morpheus gives more spectrum, peptide, and protein identifications at a 1% false discovery rate (FDR) than Mascot, Open Mass Spectrometry Search Algorithm (OMSSA), and Sequest. Additionally, Morpheus is 1.5 to 4.6 times faster, depending on the data set, than the next fastest algorithm, OMSSA. Morpheus was developed in C# .NET and is available free and open source under a permissive license.
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Cites
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
Mass spectrometry-based proteomics
Aebersold, R., & Mann, M. (2003) · Nature · doi:10.1038/nature01511 · Cited by 6,955
Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925
Semi-supervised learning for peptide identification from shotgun proteomics datasets
Käll, L., Canterbury, J. D., Weston, J., Noble, W. S., & MacCoss, M. J. (2007) · Nature Methods · doi:10.1038/nmeth1113 · Cited by 2,424
ProteoWizard: open source software for rapid proteomics tools development
Kessner, D., Chambers, M., Burke, R., Agus, D., & Mallick, P. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn323 · Cited by 2,024
Interpretation of Shotgun Proteomic Data
Nesvizhskii, A. I., & Aebersold, R. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r500012-mcp200 · Cited by 1,025
Michalski, A., Damoc, E., Hauschild, J.-P., Lange, O., Wieghaus, A., Makarov, A., Nagaraj, N., Cox, J., Mann, M., & Horning, S. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.011015 · Cited by 832
A dual pressure linear ion trap orbitrap instrument with very high sequencing speed
Olsen, J. V., Schwartz, J. C., Griep-Raming, J., Nielsen, M. L., Damoc, E., Denisov, E., Lange, O., Remes, P., Taylor, D., Splendore, M., et al. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900375-mcp200 · Cited by 464
Precision proteomics: The case for high resolution and high mass accuracy
Mann, M., & Kelleher, N. L. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800788105 · Cited by 450
Cited by
Protein Analysis by Shotgun/Bottom-up Proteomics
Zhang, Y., Fonslow, B. R., Shan, B., Baek, M.-C., & Yates, J. R. (2013) · Chemical Reviews · doi:10.1021/cr3003533 · Cited by 1,491
MS-GF+ makes progress towards a universal database search tool for proteomics
Kim, S., & Pevzner, P. A. (2014) · Nature Communications · doi:10.1038/ncomms6277 · Cited by 1,098
Proteogenomic characterization of pancreatic ductal adenocarcinoma
Cao, L., Huang, C., Cui Zhou, D., Hu, Y., Lih, T. M., Savage, S. R., Krug, K., Clark, D. J., Schnaubelt, M., Chen, L., et al. (2021) · Cell · doi:10.1016/j.cell.2021.08.023 · Cited by 578
MS Amanda, a Universal Identification Algorithm Optimized for High Accuracy Tandem Mass Spectra
Dorfer, V., Pichler, P., Stranzl, T., Stadlmann, J., Taus, T., Winkler, S., & Mechtler, K. (2014) · Journal of Proteome Research · doi:10.1021/pr500202e · Cited by 490
Serine ADP-ribosylation depends on HPF1
Bonfiglio, J. J., Fontana, P., Zhang, Q., Colby, T., Gibbs-Seymour, I., Atanassov, I., Bartlett, E., Zaja, R., Ahel, I., & Matic, I. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.01.003 · Cited by 352
Metadata
- Authors
- Wenger, C. D., & Coon, J. J.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-01-31
- Volume
- 12
- Issue
- 3
- Pages
- 1377-1386
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2090402744
- Cited by
- 159
- References
- 9
- FWCI
- 7.57
- Type
- journal article
- Language
- en
- Open access
- green
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