Pál Riba

56 total papers · 1.1k total citations
44 papers, 935 citations indexed

About

Pál Riba is a scholar working on Physiology, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Pál Riba has authored 44 papers receiving a total of 935 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Physiology, 27 papers in Cellular and Molecular Neuroscience and 20 papers in Molecular Biology. Recurrent topics in Pál Riba's work include Pain Mechanisms and Treatments (26 papers), Neuropeptides and Animal Physiology (25 papers) and Pharmacological Receptor Mechanisms and Effects (10 papers). Pál Riba is often cited by papers focused on Pain Mechanisms and Treatments (26 papers), Neuropeptides and Animal Physiology (25 papers) and Pharmacological Receptor Mechanisms and Effects (10 papers). Pál Riba collaborates with scholars based in Hungary, Austria and Germany. Pál Riba's co-authors include Valéria Kecskeméti, György Bagdy, Rita Jakus, Susanna Fürst, Mahmoud Al‐Khrasani, Kornél Király, Mariana Spetea, Helmut Schmidhammer, Júlia Tímár and Nancy M. Lee and has published in prestigious journals such as International Journal of Molecular Sciences, Journal of Medicinal Chemistry and Journal of Neurochemistry.

In The Last Decade

Pál Riba

43 papers receiving 915 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Pál Riba 577 380 345 206 106 44 935
M. K. Paasonen 345 0.6× 304 0.8× 203 0.6× 139 0.7× 126 1.2× 60 1.1k
J. Gibert‐Rahola 638 1.1× 343 0.9× 452 1.3× 117 0.6× 53 0.5× 48 1.2k
Piotr Tutka 400 0.7× 442 1.2× 311 0.9× 197 1.0× 78 0.7× 56 977
F. Cankat Tulunay 681 1.2× 425 1.1× 458 1.3× 95 0.5× 46 0.4× 50 1.1k
Ze‐Hui Gong 451 0.8× 458 1.2× 234 0.7× 111 0.5× 43 0.4× 62 956
A. Di Giannuario 404 0.7× 348 0.9× 290 0.8× 73 0.4× 57 0.5× 45 936
Karl Verebey 378 0.7× 258 0.7× 185 0.5× 97 0.5× 66 0.6× 40 1.1k
Tomio Segawa 805 1.4× 645 1.7× 203 0.6× 107 0.5× 44 0.4× 74 1.2k
Marc Verleye 442 0.8× 308 0.8× 210 0.6× 84 0.4× 53 0.5× 44 1.0k
J. Bruinvels 417 0.7× 326 0.9× 131 0.4× 119 0.6× 55 0.5× 54 845

Countries citing papers authored by Pál Riba

Since Specialization
Citations

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

Fields of papers citing papers by Pál Riba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pál Riba

This figure shows the co-authorship network connecting the top 25 collaborators of Pál Riba. A scholar is included among the top collaborators of Pál Riba based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pál Riba. Pál Riba is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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