K. Graf

19 papers receiving 1.1k citations

Peers

K. Graf
Comparison fields: 5 of 81
  • Cardiology and Cardiovascular Medicine 290
  • Immunology and Allergy 80
  • Cancer Research 145
  • Molecular Biology 545
  • Genetics 76
Replace Kunio Yasunaga with:
Kunio Yasunaga Japan
J. Fingerle Germany
Eugenia Shvartz United States
Richard Magid United States
Megan Podowski United States
Adam J. Belanger United States
Yevgenia Tesmenitsky United States
Sarah L. Tressel United States
Pia Leppänen Finland
Chongxiu Sun United States
K. Graf relative to Kunio Yasunaga Japan Kunio Yasunaga's profile →
Citations per field
00.5×2.7×
Kunio Yasunaga · 1×
Citations per year

Countries citing papers authored by K. Graf

Since Specialization
Citations

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

Fields of papers citing papers by K. Graf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996438
2 1996218
3 200497
4 199363
5 200552
6 199649
7 199443
8 200725
9 199824
10 199520
11 199317
12 199414
13 199713
14 199610
15
Targeted ED-B fibronectin SPECT in vivo imaging in experimental atherosclerosis.
20154
16 20032
17 19951
18 19721
19 20031
20 20070

About K. Graf

K. Graf is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology, Genetics, Oncology and Surgery, having authored 21 papers that have together received 1.1k indexed citations. Recurring topics across this work include Coagulation, Bradykinin, Polyphosphates, and Angioedema (3 papers), Protease and Inhibitor Mechanisms (2 papers), Receptor Mechanisms and Signaling (2 papers), Renin-Angiotensin System Studies (2 papers), Peptidase Inhibition and Analysis (2 papers), Neuropeptides and Animal Physiology (2 papers), Cardiac Fibrosis and Remodeling (2 papers) and Nitric Oxide and Endothelin Effects (1 paper). The work is most often cited by research in Cardiology and Cardiovascular Medicine (290 citations), Immunology and Allergy (80 citations), Cancer Research (145 citations), Molecular Biology (545 citations) and Genetics (76 citations). K. Graf has collaborated with scholars based in Germany, United States and Austria. Frequent co-authors include Willa A. Hsueh, Woerner P. Meehan, R E Law, David P. Faxon, William D. Coats, Daniel Wüthrich, Nobuyuki Ashizawa, Eckart Fleck, Tatsuya Nunohiro and Tai‐Lan Tuan. Their work appears in journals such as Cardiovascular Research, American Journal of Physiology-Heart and Circulatory Physiology, Clinical Chemistry and Laboratory Medicine (CCLM), Journal of Clinical Investigation and European Heart Journal.

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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