Nina Graffmann

887 citations
30 papers · 472 · h-index 13

Impact in

  • Hepatology top 10%
    • Liver physiology and pathology
    • Mesenchymal stem cell research

Papers in

    • Pluripotent Stem Cells Research 13
    • Renal and related cancers 10
    • Epigenetics and DNA Methylation 5
    • CRISPR and Genetic Engineering 5
    • Pancreatic function and diabetes 6

Nina Graffmann

27 papers receiving 469 citations

Peers

Nina Graffmann
Comparison fields: 5 of 72
  • Hepatology 76
  • Genetics 67
  • Developmental Neuroscience 15
  • Molecular Biology 249
  • Surgery 129
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Panpan Cen China
Karolien Buyl Belgium
Hongli Song China
Yaojun Wang China
Injoo Hwang South Korea
Guangxin Jin China
Adil N. Irani United States
Fuxiang Yu China
Li Ling China
Lucía Cordero-Espinoza United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Nina Graffmann

Since Specialization
Citations

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

Fields of papers citing papers by Nina Graffmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201681
2 200844
3 202143
4 201640
5 202033
6 201029
7 201227
8 201827
9 202221
10 201820
11 201816
12 202214
13 202012
14 201810
15 20209
16 20068
17 20188
18 20187
19 20155
20 20234

About Nina Graffmann

Nina Graffmann is a scholar working on Molecular Biology, Surgery, Epidemiology, Biochemistry and Hepatology, having authored 30 papers that have together received 472 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (13 papers), Renal and related cancers (10 papers), Pancreatic function and diabetes (6 papers), Epigenetics and DNA Methylation (5 papers), CRISPR and Genetic Engineering (5 papers), Liver Disease Diagnosis and Treatment (4 papers), Lipid metabolism and biosynthesis (3 papers) and Liver physiology and pathology (3 papers). The work is most often cited by research in Hepatology (76 citations), Genetics (67 citations), Developmental Neuroscience (15 citations), Molecular Biology (249 citations) and Surgery (129 citations). Nina Graffmann has collaborated with scholars based in Germany, United Kingdom and Austria. Frequent co-authors include James Adjaye, Wasco Wruck, Markus Uhrberg, Lucas‐Sebastian Spitzhorn, Simeon Santourlidis, Hans‐Ingo Trompeter, Martina Bohndorf, Lisa Nguyen, Lars Erichsen and Sarah Ferber. Their work appears in journals such as Stem Cell Research, Frontiers in Cell and Developmental Biology, Stem Cells and Development, Stem Cells and Scientific Reports.

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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