Csaba Leranth

62 papers receiving 4.4k citations

Peers

Csaba Leranth
Comparison fields: 5 of 125
  • Behavioral Neuroscience 711
  • Endocrine and Autonomic Systems 687
  • Cellular and Molecular Neuroscience 1.8k
  • Developmental Neuroscience 353
  • Reproductive Medicine 657
Replace Tibor Hajszán with:
Tibor Hajszán United States
Dean E. Dluzen United States
Fukuko Kimura Japan
Maya Frankfurt United States
Richard E. Harlan United States
Csaba Léránth United States
Dai Mitsushima Japan
Dipak K. Sarkar United States
Nancy G. Weiland United States
Toshiya Funabashi Japan
Csaba Leranth relative to Tibor Hajszán United States Tibor Hajszán's profile →
Citations per field
00.5×1.5×2.4×
Tibor Hajszán · 1×
Citations per year

Countries citing papers authored by Csaba Leranth

Since Specialization
Citations

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

Fields of papers citing papers by Csaba Leranth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1989365
2 2006343
3 1986223
4
"Dark" Purkinje cells of the cerebellar cortex.
1970220
5 2005207
6 1996204
7 2004198
8 2008188
9 2006179
10 1988178
11 2005175
12 2008163
13 1990157
14 1992140
15 1992130
16 200299
17 201091
18 200584
19 199573
20 198773

About Csaba Leranth

Csaba Leranth is a scholar working on Cellular and Molecular Neuroscience, Behavioral Neuroscience, Genetics, Molecular Biology and Social Psychology, having authored 62 papers that have together received 4.4k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (18 papers), Stress Responses and Cortisol (13 papers), Estrogen and related hormone effects (12 papers), Neuropeptides and Animal Physiology (11 papers), Neuroendocrine regulation and behavior (10 papers), Hypothalamic control of reproductive hormones (8 papers), Menopause: Health Impacts and Treatments (8 papers) and Effects and risks of endocrine disrupting chemicals (7 papers). The work is most often cited by research in Behavioral Neuroscience (711 citations), Endocrine and Autonomic Systems (687 citations), Cellular and Molecular Neuroscience (1.8k citations), Developmental Neuroscience (353 citations) and Reproductive Medicine (657 citations). Csaba Leranth has collaborated with scholars based in United States, Hungary and Canada. Frequent co-authors include Tibor Hajszán, Neil J. MacLusky, Frederick Naftolin, Tamás L. Horváth, J. Hámori, Susannah Williams, Marya Shanabrough, Klara Szigeti‐Buck, N. Mons and P.S. Goldman-Rakic. Their work appears in journals such as Neuroscience, Endocrinology, The Journal of Comparative Neurology, Brain Research 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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