Frieda Ungar

587 citations
29 papers · 451 · h-index 13

Impact in

Papers in

Frieda Ungar

29 papers receiving 394 citations

Peers

Frieda Ungar
Comparison fields: 5 of 81
  • Cellular and Molecular Neuroscience 147
  • Biochemistry 54
  • Sensory Systems 24
  • Physiology 20
  • Clinical Biochemistry 28
Replace V. Z. Gorkin with:
V. Z. Gorkin Russia
Shu Wen Li United States
Jeffrey K. Saelens Switzerland
Tarou Ogurusu Japan
John L. Sawyer United States
C.J. Coles United States
M. Wolfensberger Switzerland
Jenő Tóth United States
R. PELLICCIARI Italy
William F. Bridgers United States
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Citations per field
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Citations per year

Countries citing papers authored by Frieda Ungar

Since Specialization
Citations

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

Fields of papers citing papers by Frieda Ungar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Frieda Ungar, 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 Frieda Ungar Line = papers co-authored together Frieda Ungar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 196850
2 196942
3 196537
4 196037
5 196435
6 196133
7 197224
8 197323
9 197120
10 196615
11 197014
12 197314
13
Ontogenesis of serotonergic systems in rat brain.
197613
14 196112
15
Tyramine-binding by synaptosomes from rat brain: effect of centrally active drugs.
197710
16 19639
17 19689
18 19588
19 19707
20
Preliminary studies of the sodium borohydride stabilizable binding of phenylethylamine and tyramine to brain preparations.
19787

About Frieda Ungar

Frieda Ungar is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Organic Chemistry, Pharmacology and Physiology, having authored 29 papers that have together received 451 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (12 papers), Neurotransmitter Receptor Influence on Behavior (9 papers), Enzyme function and inhibition (7 papers), Receptor Mechanisms and Signaling (5 papers), Amino Acid Enzymes and Metabolism (3 papers), Adenosine and Purinergic Signaling (3 papers), Cholinesterase and Neurodegenerative Diseases (2 papers) and Olfactory and Sensory Function Studies (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (147 citations), Biochemistry (54 citations), Sensory Systems (24 citations), Physiology (20 citations) and Clinical Biochemistry (28 citations). Frieda Ungar has collaborated with scholars based in United States, Greece and United Kingdom. Frequent co-authors include Spyridon G.A. Alivisatos, Boris Tabakoff, Prahlad K. Seth, LeRoy P. Levitt, William J. Giardina, Héctor Sabelli, P.K. Seth, Owen Callaghan, Surendra S. Parmar and B Ungár. Their work appears in journals such as Nature, Biochemical Pharmacology, Journal of Biological Chemistry, Biochemistry and Biochemical and Biophysical Research Communications.

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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