Michael Graf

1.8k citations
23 papers · 1.3k · h-index 16

Impact in

Papers in

    • RNA and protein synthesis mechanisms 14
    • Enzyme Catalysis and Immobilization 4
    • RNA modifications and cancer 4
    • Biochemical and Structural Characterization 3
    • Enzyme-mediated dye degradation 6

Michael Graf

23 papers receiving 1.3k citations

Peers

Michael Graf
Comparison fields: 5 of 91
  • Microbiology 509
  • Molecular Medicine 104
  • Molecular Biology 1.0k
  • Structural Biology 14
  • Genetics 173
Replace Matthieu G. Gagnon with:
Matthieu G. Gagnon United States
Bernard Clantin France
Stefanie Wagner Germany
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Yen‐Pang Hsu United States
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Citations per field
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Citations per year

Countries citing papers authored by Michael Graf

Since Specialization
Citations

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

Fields of papers citing papers by Michael Graf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michael Graf, 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 Michael Graf Line = papers co-authored together Michael Graf links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017162
2 2015152
3 2017139
4 2017120
5 2016101
6 201993
7 201690
8 201875
9 202161
10 201247
11 201845
12 201643
13 201642
14 201328
15 201922
16 201616
17 201514
18 201612
19 201611
20 201410

About Michael Graf

Michael Graf is a scholar working on Molecular Biology, Plant Science, Microbiology, Genetics and Ecology, having authored 23 papers that have together received 1.3k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (14 papers), Enzyme-mediated dye degradation (6 papers), Antimicrobial Peptides and Activities (5 papers), Enzyme Catalysis and Immobilization (4 papers), Bacterial Genetics and Biotechnology (4 papers), RNA modifications and cancer (4 papers), Biochemical and Structural Characterization (3 papers) and Bacteriophages and microbial interactions (3 papers). The work is most often cited by research in Microbiology (509 citations), Molecular Medicine (104 citations), Molecular Biology (1.0k citations), Structural Biology (14 citations) and Genetics (173 citations). Michael Graf has collaborated with scholars based in Germany, Austria and United States. Frequent co-authors include Daniel N. Wilson, C.A. Innis, Stefan Arenz, Fabian Nguyen, A. Carolin Seefeldt, Paul Huter, Gilles Guichard, Roland Beckmann, Mario Mardirossian and Marco Scocchi. Their work appears in journals such as Nucleic Acids Research, Nature Communications, Biochemistry, Nature Structural & Molecular Biology and Proceedings of the National Academy of Sciences.

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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