Kim M. Brown

10 total papers · 934 total citations
8 papers, 706 citations indexed

About

Kim M. Brown is a scholar working on Molecular Biology, Plant Science and Pharmacology. According to data from OpenAlex, Kim M. Brown has authored 8 papers receiving a total of 706 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Plant Science and 2 papers in Pharmacology. Recurrent topics in Kim M. Brown's work include Receptor Mechanisms and Signaling (4 papers), Phosphodiesterase function and regulation (4 papers) and Enzyme-mediated dye degradation (3 papers). Kim M. Brown is often cited by papers focused on Receptor Mechanisms and Signaling (4 papers), Phosphodiesterase function and regulation (4 papers) and Enzyme-mediated dye degradation (3 papers). Kim M. Brown collaborates with scholars based in United States, United Kingdom and Denmark. Kim M. Brown's co-authors include George S. Baillie, Miles D. Houslay, Sakari Kauppinen, Stephen H.M. Brown, Torben Halkier, Devan Jaganath, Andrew Daniels, Xiang‐Yao Li, Min Zhuo and Tao Chen and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Molecular and Cellular Biology.

In The Last Decade

Kim M. Brown

8 papers receiving 681 citations

Author Peers

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

Author						Papers	Cites
Kim M. Brown	222	216	214	166	154	8	706
Thomas N. Gaitanos	306 1.4×	227 1.1×	27 0.1×	182 1.1×	69 0.4×	8	797
Kyle C. Schmitt	475 2.1×	58 0.3×	113 0.5×	399 2.4×	24 0.2×	12	803
Cindy Lin	511 2.3×	141 0.7×	45 0.2×	130 0.8×	21 0.1×	19	899
Wanling Peng	286 1.3×	198 0.9×	44 0.2×	268 1.6×	11 0.1×	21	909
Jeffrey Reinking	319 1.4×	59 0.3×	21 0.1×	283 1.7×	22 0.1×	17	742
Jan Lehmbeck	542 2.4×	107 0.5×	142 0.7×	37 0.2×	233 1.5×	28	872
Ane M. Gabilondo	465 2.1×	27 0.1×	51 0.2×	427 2.6×	31 0.2×	30	757
Shuichi Takizawa	277 1.2×	124 0.6×	30 0.1×	227 1.4×	127 0.8×	10	653
Thu Ha Pham	178 0.8×	65 0.3×	113 0.5×	231 1.4×	15 0.1×	14	762
B. Bourrié	247 1.1×	92 0.4×	53 0.2×	334 2.0×	126 0.8×	11	779

Countries citing papers authored by Kim M. Brown

Since Specialization

Citations

This map shows the geographic impact of Kim 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 Kim 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 Kim M. Brown more than expected).

Fields of papers citing papers by Kim M. Brown

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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

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