Natalya M. Kogan

35 total papers · 1.2k total citations
27 papers, 964 citations indexed

About

Natalya M. Kogan is a scholar working on Pharmacology, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Natalya M. Kogan has authored 27 papers receiving a total of 964 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Pharmacology, 8 papers in Molecular Biology and 5 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Natalya M. Kogan's work include Cannabis and Cannabinoid Research (15 papers), Diet, Metabolism, and Disease (5 papers) and Neurotransmitter Receptor Influence on Behavior (3 papers). Natalya M. Kogan is often cited by papers focused on Cannabis and Cannabinoid Research (15 papers), Diet, Metabolism, and Disease (5 papers) and Neurotransmitter Receptor Influence on Behavior (3 papers). Natalya M. Kogan collaborates with scholars based in Israel, United States and France. Natalya M. Kogan's co-authors include Raphael Mechoulam, Pál Pacher, Michael Schlesinger, Maximilian Peters, Ruth Rabinowitz, Arieh Moussaieff, Daniel Aberdam, Péter Sándor, Dan Gibson and Manuel Guzmán and has published in prestigious journals such as Proceedings of the National Academy of Sciences, American Journal of Clinical Nutrition and Journal of Cell Science.

In The Last Decade

Natalya M. Kogan

26 papers receiving 941 citations

Author Peers

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

Author Last Decade Papers Cites
Natalya M. Kogan 645 232 201 129 114 27 964
Carmen Navarrete 717 1.1× 321 1.4× 293 1.5× 180 1.4× 101 0.9× 33 1.2k
María Gómez‐Cañas 798 1.2× 277 1.2× 366 1.8× 148 1.1× 98 0.9× 33 1.1k
Guillermo Moreno‐Sanz 813 1.3× 218 0.9× 279 1.4× 105 0.8× 116 1.0× 26 1.0k
Ronald G. Rossetti 481 0.7× 273 1.2× 160 0.8× 62 0.5× 121 1.1× 26 1.1k
Irene Cantarero 445 0.7× 254 1.1× 197 1.0× 125 1.0× 162 1.4× 26 896
María L. Bellido 567 0.9× 471 2.0× 302 1.5× 290 2.2× 73 0.6× 29 1.2k
Jin Fu 557 0.9× 411 1.8× 153 0.8× 82 0.6× 112 1.0× 26 1.1k
Yun K. Hahn 471 0.7× 245 1.1× 290 1.4× 45 0.3× 110 1.0× 21 1.1k
Yuko Kurahashi 713 1.1× 124 0.5× 270 1.3× 143 1.1× 139 1.2× 20 869
Sherry Shu‐Jung Hu 723 1.1× 184 0.8× 338 1.7× 87 0.7× 91 0.8× 22 969

Countries citing papers authored by Natalya M. Kogan

Since Specialization
Citations

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

Fields of papers citing papers by Natalya M. Kogan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Natalya M. Kogan. 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 Natalya M. Kogan. The network helps show where Natalya M. Kogan may publish in the future.

Co-authorship network of co-authors of Natalya M. Kogan

This figure shows the co-authorship network connecting the top 25 collaborators of Natalya M. Kogan. A scholar is included among the top collaborators of Natalya M. Kogan 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 Natalya M. Kogan. Natalya M. Kogan 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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