E. Kaltschmidt

2.4k citations
16 papers · 2.2k indexed · 1 hit paper · h-index 14
    • RNA and protein synthesis mechanisms 16
    • RNA modifications and cancer 4
    • Genomics and Phylogenetic Studies 4
    • Machine Learning in Bioinformatics 1
  • Genetics top 5%
  • Ecology top 5%
    • Bacteriophages and microbial interactions 5
    • Mass Spectrometry Techniques and Applications 4
    • Peptidase Inhibition and Analysis 2
    • Probiotics and Fermented Foods 2

E. Kaltschmidt

16 papers receiving 1.9k citations

Hit Papers

Ribosomal proteins. VII1.0k19702026198820072505007501000

Peers

E. Kaltschmidt
Comparison fields: 5 of 82
  • Molecular Biology 2.1k
  • Genetics 502
  • Ecology 380
  • Spectroscopy 216
  • Oncology 230
Replace R.A. Garrett with:
R.A. Garrett Germany
James Ofengand United States
Guy Fayat France
Gisela Kramer United States
J.P. Ebel France
Richard H. Buckingham France
Lawrence Kahan United States
Yves Méchulam France
M. Takanami Japan
Lasse Lindahl United States
E. Kaltschmidt relative to R.A. Garrett Germany R.A. Garrett's profile →
Citations per field
00.5×3.2×
R.A. Garrett · 1×
Citations per year

Countries citing papers authored by E. Kaltschmidt

Since Specialization
Citations

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

Fields of papers citing papers by E. Kaltschmidt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by E. Kaltschmidt. 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 E. Kaltschmidt. The network helps show where E. Kaltschmidt may publish in the future.

Co-authorship network

The 15 scholars most cited alongside E. Kaltschmidt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with E. Kaltschmidt Line = papers co-authored together E. Kaltschmidt links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 197425
2 19722
3 197233
4 197249
5 19716
6 1971105
7 1971102
8 1971151
9 197184
10
Ribosomal proteins. VIIbreakdown →
19701036
11 1970112
12 1970116
13 1970240
14 197038
15 196923
16 196759

About E. Kaltschmidt

E. Kaltschmidt is a scholar working on Spectroscopy, Molecular Biology and Ecology, having authored 16 papers that have together received 2.2k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (16 papers), Bacteriophages and microbial interactions (5 papers), RNA modifications and cancer (4 papers), Genomics and Phylogenetic Studies (4 papers), Mass Spectrometry Techniques and Applications (4 papers), Probiotics and Fermented Foods (2 papers), Peptidase Inhibition and Analysis (2 papers) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Molecular Biology (2.1k citations), Genetics (502 citations) and Ecology (380 citations). E. Kaltschmidt has collaborated with scholars based in Germany, United States and Sweden. Frequent co-authors include H. G. Wittmann, M. Dzionara, I Hindennach, Michio Nomura, W. Held, H Nashimoto, Lawrence Kahan, Georg Stöffler, D. Donner and Edward A. Birge. Their work appears in journals such as Analytical Biochemistry, Proceedings of the National Academy of Sciences, Biochimie, European Journal of Biochemistry and Journal of Molecular Biology.

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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