L. Gráf

1.2k citations
39 papers · 950 · h-index 16

Impact in

Papers in

L. Gráf

38 papers receiving 832 citations

Peers

L. Gráf
Comparison fields: 5 of 87
  • Cellular and Molecular Neuroscience 433
  • Molecular Biology 657
  • Physiology 151
  • Endocrine and Autonomic Systems 38
  • Reproductive Medicine 46
Replace Guy P. E. Tell with:
Guy P. E. Tell France
J Rathé Belgium
Takushi X. Watanabe Japan
Jean Camus Belgium
M L Toews United States
Atsushi Nagahisa United States
M. D. A. FINNIE United Kingdom
John Krupinski United States
Francisco Barros Spain
Kenneth Thirstrup Denmark
L. Gráf relative to Guy P. E. Tell France Guy P. E. Tell's profile →
Citations per field
00.5×
Guy P. E. Tell · 1×
Citations per year

Countries citing papers authored by L. Gráf

Since Specialization
Citations

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

Fields of papers citing papers by L. Gráf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1988144
2 1977123
3 1976115
4 199376
5 197762
6 197153
7 199441
8 197234
9 197934
10 196825
11 197922
12 197322
13 197321
14 199420
15 198118
16 196917
17 197714
18 197613
19 198211
20 198510

About L. Gráf

L. Gráf is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Oncology, Endocrinology, Diabetes and Metabolism and Psychiatry and Mental health, having authored 39 papers that have together received 950 indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (11 papers), Receptor Mechanisms and Signaling (10 papers), Chemical Synthesis and Analysis (4 papers), Peptidase Inhibition and Analysis (3 papers), Pharmacological Effects and Toxicity Studies (3 papers), Epilepsy research and treatment (3 papers), Growth Hormone and Insulin-like Growth Factors (3 papers) and Hypothalamic control of reproductive hormones (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (433 citations), Molecular Biology (657 citations), Physiology (151 citations), Endocrine and Autonomic Systems (38 citations) and Reproductive Medicine (46 citations). L. Gráf has collaborated with scholars based in Hungary, United States and Germany. Frequent co-authors include S. Bajusz, Zsuzsa Dunai-Kovàcs, József I. Székely, András Z. Rónai, G Cseh, Erzsébet Barát, Á. Patthy, A Jancsó, Ilona Berzétei and Katalin Pintér. Their work appears in journals such as FEBS Letters, Proceedings of the National Academy of Sciences, Journal of Bacteriology, Archives of Biochemistry and Biophysics and European Journal of Pharmacology.

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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