Higher-energy C-trap dissociation for peptide modification analysis
Impact in
- Spectroscopy 484
Classified as
- Journal
- Nature Methods
In The Last Decade
doi.org/10.1038/nmeth1060 →Countries where authors are citing Higher-energy C-trap dissociation for peptide modification analysis
This map shows the geographic impact of Higher-energy C-trap dissociation for peptide modification analysis. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Higher-energy C-trap dissociation for peptide modification analysis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Higher-energy C-trap dissociation for peptide modification analysis more than expected).
Fields of papers citing Higher-energy C-trap dissociation for peptide modification analysis
This network shows the impact of Higher-energy C-trap dissociation for peptide modification analysis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Higher-energy C-trap dissociation for peptide modification analysis.
About Higher-energy C-trap dissociation for peptide modification analysis
This paper, published in 2007, received 755 indexed citations . Written by Jesper V. Olsen, Boris Maček, Oliver Lange, Alexander Makarov, Stevan Horning and Matthias Mann covering the research area of Molecular Biology and Spectroscopy. It is primarily cited by scholars working on Molecular Biology (537 citations), Spectroscopy (484 citations), Cell Biology (52 citations), Oncology (34 citations) and Biomedical Engineering (28 citations). Published in Nature Methods.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/10.1038/nmeth1060.