The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Characterization by Tandem Mass Spectrometry of Structural Modifications in Proteins
Abstract
Tandem mass spectrometry can be used to solve a number of protein structural problems that are not amenable to conventional methods for amino acid sequencing. Typical problems that use this approach involve characterization of peptides with blocked amino termini or peptides that have been otherwise posttranslationally processed, such as, by phosphorylation or sulfation. The structure and homogeneity of synthetic peptides can also be evaluated. Since peptides can be selectively characterized in the presence of other peptides or contaminants, the need for extensive purification is reduced or eliminated.
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Citations
Cites
Sanger, F., & Tuppy, H. (1951) · Biochemical Journal · doi:10.1042/bj0490463 · Cited by 784
Cited by
Dongré, A. R., Jones, J. L., Somogyi, Á., & Wysocki, V. H. (1996) · Journal of the American Chemical Society · doi:10.1021/ja9542193 · Cited by 894
Anchoring of Surface Proteins to the Cell Wall of Staphylococcus aureus
Ton-That, H., Mazmanian, S. K., Faull, K. F., & Schneewind, O. (2000) · Journal of Biological Chemistry · doi:10.1074/jbc.275.13.9876 · Cited by 359
Metadata
- Authors
- Biemann, K., & Scoble, H. A.
- Venue
- Science
- Published
- 1987-08-28
- Volume
- 237
- Issue
- 4818
- Pages
- 992-998
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2087981895
- Cited by
- 365
- References
- 1
- FWCI
- 21.05
- Type
- journal article
- Language
- en
- Open access
- closed
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- Biemann, K., & Scoble, H. A. (1987). Characterization by Tandem Mass Spectrometry of Structural Modifications in Proteins. Science. https://doi.org/10.1126/science.3303336
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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.
