The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Universal and Confident Phosphorylation Site Localization Using phosphoRS
Open accessAbstract
An algorithm for the assignment of phosphorylation sites in peptides is described. The program uses tandem mass spectrometry data in conjunction with the respective peptide sequences to calculate site probabilities for all potential phosphorylation sites. Tandem mass spectra from synthetic phosphopeptides were used for optimization of the scoring parameters employing all commonly used fragmentation techniques. Calculation of probabilities was adapted to the different fragmentation methods and to the maximum mass deviation of the analysis. The software includes a novel approach to peak extraction, required for matching experimental data to the theoretical values of all isoforms, by defining individual peak depths for the different regions of the tandem mass spectrum. Mixtures of synthetic phosphopeptides were used to validate the program by calculation of its false localization rate versus site probability cutoff characteristic. Notably, the empirical obtained precision was higher than indicated by the applied probability cutoff. In addition, the performance of the algorithm was compared to existing approaches to site localization such as Ascore. In order to assess the practical applicability of the algorithm to large data sets, phosphopeptides from a biological sample were analyzed, localizing more than 3000 nonredundant phosphorylation sites. Finally, the results obtained for the different fragmentation methods and localization tools were compared and discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925
Beausoleil, S. A., Villén, J., Gerber, S. A., Rush, J., & Gygi, S. P. (2006) · Nature Biotechnology · doi:10.1038/nbt1240 · Cited by 1,577
Mass spectrometry in high-throughput proteomics: ready for the big time
Nilsson, T., Mann, M., Aebersold, R., Yates, J. R., Bairoch, A., & Bergeron, J. J. M. (2010) · Nature Methods · doi:10.1038/nmeth0910-681 · Cited by 470
Catch me if you can: Mass spectrometry‐based phosphoproteomics and quantification strategies
Eyrich, B., Sickmann, A., & Zahedi, R. P. (2011) · PROTEOMICS · doi:10.1002/pmic.201000489 · Cited by 104
Cited by
PKM2 Phosphorylates Histone H3 and Promotes Gene Transcription and Tumorigenesis
Yang, W., Xia, Y., Hawke, D., Li, X., Liang, J., Xing, D., Aldape, K., Hunter, T., Alfred Yung, W. K., & Lu, Z. (2012) · Cell · doi:10.1016/j.cell.2012.07.018 · Cited by 846
Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression
Bai, B., Wang, X., Li, Y., Chen, P.-C., Yu, K., Dey, K. K., Yarbro, J. M., Han, X., Lutz, B. M., Rao, S., et al. (2020) · Neuron · doi:10.1016/j.neuron.2019.12.015 · Cited by 565
“Phosphosite Localization by the JUMPl Program—To evaluate the confidence of assigned individual phosphosites in peptides, we generated the JUMPl program using the concept of the phosphoRS algorithm (Taus et al., 2011) to calculate phosphosite localization scores (Lscore, 0-100%) for each PSM.”
MethodChen, Y.-J., Roumeliotis, T. I., Chang, Y.-H., Chen, C.-T., Han, C.-L., Lin, M.-H., Chen, H.-W., Chang, G.-C., Chang, Y.-L., Wu, C.-T., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.012 · Cited by 382
Krajewska, M., Dries, R., Grassetti, A. V., Dust, S., Gao, Y., Huang, H., Sharma, B., Day, D. S., Kwiatkowski, N., Pomaville, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09703-y · Cited by 281
Phosphoproteomics in the Age of Rapid and Deep Proteome Profiling
Riley, N. M., & Coon, J. J. (2016) · Analytical Chemistry · doi:10.1021/acs.analchem.5b04123 · Cited by 265
Thompson, A., Wölmer, N., Koncarevic, S., Selzer, S., Böhm, G., Legner, H., Schmid, P., Kienle, S., Penning, P., Höhle, C., et al. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b04474 · Cited by 186
Stewart, E., McEvoy, J., Wang, H., Chen, X., Honnell, V., Ocarz, M., Gordon, B., Dapper, J., Blankenship, K., Yang, Y., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.07.012 · Cited by 153
Inhibition of CBLB protects from lethal Candida albicans sepsis
Wirnsberger, G., Zwolanek, F., Asaoka, T., Kozieradzki, I., Tortola, L., Wimmer, R. A., Kavirayani, A., Fresser, F., Baier, G., Langdon, W. Y., et al. (2016) · Nature Medicine · doi:10.1038/nm.4134 · Cited by 113
Izzo, N. J., Yuede, C. M., LaBarbera, K. M., Limegrover, C. S., Rehak, C., Yurko, R., Waybright, L., Look, G., Rishton, G., Safferstein, H., et al. (2021) · Alzheimer's & Dementia · doi:10.1002/alz.12302 · Cited by 95
Proteomics Approaches for Biomarker and Drug Target Discovery in ALS and FTD
Hedl, T. J., San Gil, R., Cheng, F., Rayner, S. L., Davidson, J. M., De Luca, A., Villalva, M. D., Ecroyd, H., Walker, A. K., & Lee, A. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00548 · Cited by 87
LeDuc, R. D., Fellers, R. T., Early, B. P., Greer, J. B., Thomas, P. M., & Kelleher, N. L. (2014) · Journal of Proteome Research · doi:10.1021/pr401277r · Cited by 85
A conserved fertilization complex bridges sperm and egg in vertebrates
Deneke, V. E., Blaha, A., Lu, Y., Suwita, J. P., Draper, J. M., Phan, C. S., Panser, K., Schleiffer, A., Jacob, L., Humer, T., et al. (2024) · Cell · doi:10.1016/j.cell.2024.09.035 · Cited by 78
Kauko, O., Laajala, T. D., Jumppanen, M., Hintsanen, P., Suni, V., Haapaniemi, P., Corthals, G., Aittokallio, T., Westermarck, J., & Imanishi, S. Y. (2015) · Scientific Reports · doi:10.1038/srep13099 · Cited by 61
Quantitative phosphoproteomics uncovers dysregulated kinase networks in Alzheimer’s disease
Morshed, N., Lee, M. J., Rodriguez, F. H., Lauffenburger, D. A., Mastroeni, D., & White, F. M. (2021) · Nature Aging · doi:10.1038/s43587-021-00071-1 · Cited by 58
Kleinknecht, A., Popova, B., Lázaro, D. F., Pinho, R., Valerius, O., Outeiro, T. F., & Braus, G. H. (2016) · PLOS Genetics · doi:10.1371/journal.pgen.1006098 · Cited by 58
Yarbro, J. M., Han, X., Dasgupta, A., Yang, K., Liu, D., Shrestha, H. K., Zaman, M., Wang, Z., Yu, K., Lee, D. G., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56853-3 · Cited by 41
Chen, D., Ludwig, K. R., Krokhin, O. V., Spicer, V., Yang, Z., Shen, X., Hummon, A. B., & Sun, L. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.8b04770 · Cited by 34
Wanaguru, M., Barry, D. J., Benton, D. J., O’Reilly, N. J., & Bishop, K. N. (2018) · PLOS Pathogens · doi:10.1371/journal.ppat.1007117 · Cited by 27
Active IKKβ promotes the stability of GLI1 oncogene in diffuse large B-cell lymphoma
Agarwal, N. K., Kim, C. H., Kunkalla, K., Konno, H., Tjendra, Y., Kwon, D., Blonska, M., Kozloski, G. A., Moy, V. T., Verdun, R. E., et al. (2016) · Blood · doi:10.1182/blood-2015-07-658781 · Cited by 23
eIF4E1b is a non-canonical eIF4E protecting maternal dormant mRNAs
Lorenzo-Orts, L., Strobl, M., Steinmetz, B., Leesch, F., Pribitzer, C., Roehsner, J., Schutzbier, M., Dürnberger, G., & Pauli, A. (2023) · EMBO Reports · doi:10.1038/s44319-023-00006-4 · Cited by 23
Edwards, A. V. G., Edwards, G. J., Schwämmle, V., Saxtorph, H., & Larsen, M. R. (2014) · Journal of Proteome Research · doi:10.1021/pr4002977 · Cited by 22
Zhang, Z., Hebert, A. S., Westphall, M. S., Coon, J. J., & Dovichi, N. J. (2019) · Journal of Proteome Research · doi:10.1021/acs.jproteome.9b00244 · Cited by 22
Zebrafish Ski7 tunes RNA levels during the oocyte-to-embryo transition
Cabrera-Quio, L. E., Schleiffer, A., Mechtler, K., & Pauli, A. (2021) · PLOS Genetics · doi:10.1371/journal.pgen.1009390 · Cited by 18
Self-citationRecurrent evolution of selfishness from an essential tRNA synthetase in Caenorhabditis tropicalis
Tikanova, P., Ross, J. J., Hagmüller, A., Pühringer, F., Pliota, P., Krogull, D., Stefania, V., Hunold, M., Koreshova, A., Koller, A., et al. (2025) · Nature Ecology & Evolution · doi:10.1038/s41559-025-02894-2 · Cited by 7
Metadata
- Authors
- Taus, T., Köcher, T., Pichler, P., Paschke, C., Schmidt, A., Henrich, C., & Mechtler, K.
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-11-10
- Volume
- 10
- Issue
- 12
- Pages
- 5354-5362
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- OpenAlex
- W2325375737
- Cited by
- 870
- References
- 5
- FWCI
- 17.65
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.