Laszlo Prokai

204 papers receiving 4.9k citations

Peers

Laszlo Prokai
Comparison fields: 5 of 146
  • Behavioral Neuroscience 226
  • Endocrinology, Diabetes and Metabolism 705
  • Spectroscopy 728
  • Cellular and Molecular Neuroscience 713
  • Molecular Biology 2.3k
Replace Kevin C. Beaumont with:
Kevin C. Beaumont United States
Yi Zhang China
Theodore M. Kamenecka United States
Seymour Kaufman United States
Yoshinori Marunaka Japan
Michael B. Bolger United States
Michael D. Cameron United States
Gloriano Moneti Italy
Wen Yi China
Gregory R. J. Thatcher United States
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Citations per year

Countries citing papers authored by Laszlo Prokai

Since Specialization
Citations

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

Fields of papers citing papers by Laszlo Prokai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 209 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004451
2 2011190
3 2003153
4 2005107
5 2000103
6 1992103
7 2010103
8 201696
9 199795
10 200493
11 201079
12 201377
13 199375
14 200774
15 199571
16 199969
17 200768
18 200566
19 198566
20 200864

About Laszlo Prokai

Laszlo Prokai is a scholar working on Spectroscopy, Cellular and Molecular Neuroscience, Molecular Biology, Endocrinology, Diabetes and Metabolism and Genetics, having authored 209 papers that have together received 5.1k indexed citations. Recurring topics across this work include Mass Spectrometry Techniques and Applications (49 papers), Analytical Chemistry and Chromatography (33 papers), Estrogen and related hormone effects (30 papers), Neuropeptides and Animal Physiology (26 papers), Advanced Proteomics Techniques and Applications (22 papers), Menopause: Health Impacts and Treatments (21 papers), Receptor Mechanisms and Signaling (18 papers) and Metabolomics and Mass Spectrometry Studies (17 papers). The work is most often cited by research in Behavioral Neuroscience (226 citations), Endocrinology, Diabetes and Metabolism (705 citations), Spectroscopy (728 citations), Cellular and Molecular Neuroscience (713 citations) and Molecular Biology (2.3k citations). Laszlo Prokai has collaborated with scholars based in United States, Hungary and Australia. Frequent co-authors include Katalin Prókai-Tátrai, Stanley M. Stevens, James W. Simpkins, Nicholas S. Bodor, Alevtina D. Zharikova, William J. Simonsick, Navin Rauniyar, Pál Perjési, Ran Liu and Evelyn J. Perez. Their work appears in journals such as Journal of Chromatography A, Journal of Mass Spectrometry, International Journal of Molecular Sciences, Journal of Medicinal Chemistry and Rapid Communications in Mass Spectrometry.

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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