Daniela C. Dieterich

9.2k citations
65 papers · 4.0k indexed · 1 hit paper · h-index 27

Daniela C. Dieterich

64 papers receiving 4.0k citations

Hit Papers

Selective identification of newly synthesized proteins in...20062026201220192006200400600

Peers

Daniela C. Dieterich
Comparison fields: 5 of 120
  • Molecular Biology 2.7k
  • Cellular and Molecular Neuroscience 938
  • Organic Chemistry 936
  • Cell Biology 836
  • Spectroscopy 414
Replace Erin M. Schuman with:
Erin M. Schuman Germany
Jacques Brocard France
William N. Green United States
Zhen‐Ge Luo China
Linda C. Hsieh‐Wilson United States
André Sobel France
Masato Taoka Japan
James B. Ames United States
Toshimitsu Kawate United States
Matthias Eckhardt Germany
Daniela C. Dieterich relative to Erin M. Schuman Germany Erin M. Schuman's profile →
Citations per field
00.5×2.7×
Erin M. Schuman · 1×
Citations per year

Countries citing papers authored by Daniela C. Dieterich

Since Specialization
Citations

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

Fields of papers citing papers by Daniela C. Dieterich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniela C. Dieterich. 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 Daniela C. Dieterich. The network helps show where Daniela C. Dieterich may publish in the future.

Co-authorship network of co-authors of Daniela C. Dieterich

This figure shows the co-authorship network connecting the top 25 collaborators of Daniela C. Dieterich. A scholar is included among the top collaborators of Daniela C. Dieterich 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 Daniela C. Dieterich. Daniela C. Dieterich 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 4
2 2
3 2
4 4
5 3
6 14
7 7
8 146
9 13
10 20
11 95
12 17
13 54
14 35
15 222
16 15
17
Selective identification of newly synthesized proteins in mammalian cells using bioorthogonal noncanonical amino acid tagging (BONCAT)breakdown →
644
18 247
19 49
20 69

About Daniela C. Dieterich

Daniela C. Dieterich is a scholar working on Cellular and Molecular Neuroscience, Cell Biology and Developmental Neuroscience, having authored 65 papers that have together received 4.0k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (18 papers), Click Chemistry and Applications (17 papers) and Biotin and Related Studies (10 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (938 citations), Cell Biology (836 citations) and Molecular Biology (2.7k citations). Daniela C. Dieterich has collaborated with scholars based in Germany, United States and Israel. Frequent co-authors include David A. Tirrell, Erin M. Schuman, Johannes Graumann, A. James Link, Erin M. Schuman, Michael R. Kreutz, John T. Ngo, Eckart D. Gundelfinger, Peter Landgraf and Kimberly E. Beatty. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological 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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