Gregory M. Brown

27 total papers · 729 total citations
23 papers, 600 citations indexed

About

Gregory M. Brown is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Endocrine and Autonomic Systems. According to data from OpenAlex, Gregory M. Brown has authored 23 papers receiving a total of 600 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 7 papers in Cellular and Molecular Neuroscience and 7 papers in Endocrine and Autonomic Systems. Recurrent topics in Gregory M. Brown's work include Circadian rhythm and melatonin (6 papers), Receptor Mechanisms and Signaling (4 papers) and Electromagnetic Fields and Biological Effects (3 papers). Gregory M. Brown is often cited by papers focused on Circadian rhythm and melatonin (6 papers), Receptor Mechanisms and Signaling (4 papers) and Electromagnetic Fields and Biological Effects (3 papers). Gregory M. Brown collaborates with scholars based in Canada, United States and Hong Kong. Gregory M. Brown's co-authors include Lee J. Grota, George A. Bubenik, Shiu Fun Pang, Prahlad T. Ram, M. Silverman, Yong Song, Todd L. Kiefer, Steven M. Hill, Amit Bar‐Or and Stephen Y. W. Shiu and has published in prestigious journals such as PLoS ONE, Brain Research and The British Journal of Psychiatry.

In The Last Decade

Gregory M. Brown

23 papers receiving 577 citations

Author Peers

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

Author						Papers	Cites
Gregory M. Brown	338	130	128	119	109	23	600
Nobuhiro Kurabayashi	287 0.8×	105 0.8×	104 0.8×	53 0.4×	186 1.7×	19	555
Irina Schurov	204 0.6×	207 1.6×	116 0.9×	104 0.9×	359 3.3×	13	653
Michael V. Hogan	166 0.5×	203 1.6×	89 0.7×	116 1.0×	191 1.8×	14	568
Richard N. Ranson	174 0.5×	103 0.8×	125 1.0×	63 0.5×	72 0.7×	26	558
Do Young Kim	145 0.4×	170 1.3×	116 0.9×	121 1.0×	84 0.8×	15	596
Héctor Solís‐Chagoyán	176 0.5×	117 0.9×	83 0.6×	87 0.7×	154 1.4×	45	626
Nancy A. Garrick	145 0.4×	305 2.3×	69 0.5×	72 0.6×	145 1.3×	26	646
Hua Zhao	159 0.5×	347 2.7×	89 0.7×	168 1.4×	136 1.2×	22	623
Adeline Rachalski	102 0.3×	122 0.9×	128 1.0×	105 0.9×	159 1.5×	16	607
Anna Lena Cremer	168 0.5×	78 0.6×	135 1.1×	79 0.7×	105 1.0×	15	532

Countries citing papers authored by Gregory M. Brown

Since Specialization

Citations

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

Fields of papers citing papers by Gregory M. Brown

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gregory M. Brown

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