Karsten Schnatbaum

5.3k citations
23 papers · 1.5k indexed · 2 hit papers · h-index 12
Topics
Advanced Proteomics Techniques and Applications (8 papers)Mass Spectrometry Techniques and Applications (6 papers)Coagulation, Bradykinin, Polyphosphates, and Angioedema (5 papers)

In The Last Decade

Karsten Schnatbaum

23 papers receiving 1.5k citations

Hit Papers

Prosit: proteome-wide prediction of peptide tandem mass s...201920262021202320192019100200300400500

Peers

Karsten Schnatbaum
Comparison fields: 5 of 116
  • Molecular Biology 1.0k
  • Spectroscopy 588
  • Immunology 213
  • Oncology 135
  • Infectious Diseases 120
Replace DaRue A. Prieto with:
DaRue A. Prieto United States
Aleksey Nakorchevsky United States
Leroi V. DeSouza Canada
Chris Spahr United States
Henrik Wernérus Sweden
Rebekah L. Gundry United States
Michael H. A. Roehrl United States
Lydia Cohen Israel
Matthew Fitzgibbon United States
Stephan Arni Switzerland
Karsten Schnatbaum relative to DaRue A. Prieto United States DaRue A. Prieto's profile →
Citations per field
00.5×5.5×
DaRue A. Prieto · 1×
Citations per year

Countries citing papers authored by Karsten Schnatbaum

Since Specialization
Citations

This map shows the geographic impact of Karsten Schnatbaum's research. 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 Karsten Schnatbaum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karsten Schnatbaum more than expected).

Fields of papers citing papers by Karsten Schnatbaum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Karsten Schnatbaum. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Karsten Schnatbaum. The network helps show where Karsten Schnatbaum may publish in the future.

Co-authorship network of co-authors of Karsten Schnatbaum

This figure shows the co-authorship network connecting the top 25 collaborators of Karsten Schnatbaum. A scholar is included among the top collaborators of Karsten Schnatbaum based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Karsten Schnatbaum. Karsten Schnatbaum is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 1
3 7
4 19
5 23
6 36
7 65
8 7
9
Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learningbreakdown →
519
10 75
11 90
12 48
13 8
14 10
15 21
16 5
17 5
18 4
19 103
20 38

About Karsten Schnatbaum

Karsten Schnatbaum is a scholar working on Spectroscopy, Genetics and Transplantation, having authored 23 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (8 papers), Mass Spectrometry Techniques and Applications (6 papers) and Coagulation, Bradykinin, Polyphosphates, and Angioedema (5 papers). The work is most often cited by research in Spectroscopy (588 citations), Transplantation (57 citations) and Molecular Biology (1.0k citations). Karsten Schnatbaum has collaborated with scholars based in Germany, United Kingdom and Sweden. Frequent co-authors include Bernhard Küster, Daniel P. Zolg, Mathias Wilhelm, Tobias Schmidt, Ulf Reimer, Johannes Zerweck, Tobias Knaute, Bernard Delanghe, Stephan Aiche and Andreas Hühmer. Their work appears in journals such as Analytical Chemistry, Nature Methods and Journal of Medicinal Chemistry.

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.

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