Alvin R. King

1.2k total citations
8 papers, 716 citations indexed

About

Alvin R. King is a scholar working on Pharmacology, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Alvin R. King has authored 8 papers receiving a total of 716 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Pharmacology, 3 papers in Molecular Biology and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Alvin R. King's work include Cannabis and Cannabinoid Research (6 papers), Neurotransmitter Receptor Influence on Behavior (2 papers) and Pancreatic function and diabetes (2 papers). Alvin R. King is often cited by papers focused on Cannabis and Cannabinoid Research (6 papers), Neurotransmitter Receptor Influence on Behavior (2 papers) and Pancreatic function and diabetes (2 papers). Alvin R. King collaborates with scholars based in United States, Italy and China. Alvin R. King's co-authors include Daniele Piomelli, Pietro Paolo Sanna, Walter Francesconi, Maurizio Cammalleri, Fulvia Berton, Robert Lütjens, Cindy Simpson, Jason R. Clapper, Marco Mor and Giorgio Tarzia and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Biological Psychiatry and Journal of Medicinal Chemistry.

In The Last Decade

Alvin R. King

8 papers receiving 707 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Alvin R. King United States	8	399	331	289	93	77	8	716
Linda Console‐Bram United States	10	375 0.9×	247 0.7×	170 0.6×	69 0.7×	65 0.8×	13	563
М. Yu. Bobrov Russia	12	545 1.4×	325 1.0×	186 0.6×	81 0.9×	92 1.2×	52	861
Ankur Kapur United States	8	388 1.0×	285 0.9×	302 1.0×	102 1.1×	52 0.7×	11	613
Barbara Bosier Belgium	16	418 1.0×	345 1.0×	203 0.7×	47 0.5×	57 0.7×	20	651
Franck Désarnaud France	8	307 0.8×	292 0.9×	165 0.6×	63 0.7×	38 0.5×	9	745
Natasha L. Grimsey New Zealand	16	698 1.7×	489 1.5×	342 1.2×	134 1.4×	97 1.3×	34	935
Birthe Moesgaard Denmark	12	585 1.5×	236 0.7×	124 0.4×	154 1.7×	60 0.8×	14	711
Evgueni V. Berdyshev United States	12	643 1.6×	216 0.7×	130 0.4×	97 1.0×	105 1.4×	13	747
Huy Khang Vu Canada	6	376 0.9×	428 1.3×	218 0.8×	37 0.4×	69 0.9×	8	682
Thomas H. Burkey United States	15	489 1.2×	687 2.1×	427 1.5×	70 0.8×	101 1.3×	18	1.0k

Countries citing papers authored by Alvin R. King

Since Specialization

Citations

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

Fields of papers citing papers by Alvin R. King

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alvin R. King. 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 Alvin R. King. The network helps show where Alvin R. King may publish in the future.

Co-authorship network of co-authors of Alvin R. King

This figure shows the co-authorship network connecting the top 25 collaborators of Alvin R. King. A scholar is included among the top collaborators of Alvin R. King 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 Alvin R. King. Alvin R. King is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

Clapper, Jason R., Federica Vacondio, Alvin R. King, et al.. (2009). A Second Generation of Carbamate‐Based Fatty Acid Amide Hydrolase Inhibitors with Improved Activity in vivo. ChemMedChem. 4(9). 1505–1513. 64 indexed citations

King, Alvin R., Emmanuel Y. Dotsey, Alessio Lodola, et al.. (2009). Discovery of Potent and Reversible Monoacylglycerol Lipase Inhibitors. Chemistry & Biology. 16(10). 1045–1052. 95 indexed citations

Justinová, Zuzana, Regina A. Mangieri, Marco Bortolato, et al.. (2008). Fatty Acid Amide Hydrolase Inhibition Heightens Anandamide Signaling Without Producing Reinforcing Effects in Primates. Biological Psychiatry. 64(11). 930–937. 127 indexed citations

Mor, Marco, Alessio Lodola, Silvia Rivara, et al.. (2008). Synthesis and Quantitative Structure−Activity Relationship of Fatty Acid Amide Hydrolase Inhibitors: Modulation at the N-Portion of Biphenyl-3-yl Alkylcarbamates. Journal of Medicinal Chemistry. 51(12). 3487–3498. 66 indexed citations

King, Alvin R., Andrea Duranti, Andrea Tontini, et al.. (2007). URB602 Inhibits Monoacylglycerol Lipase and Selectively Blocks 2-Arachidonoylglycerol Degradation in Intact Brain Slices. Chemistry & Biology. 14(12). 1357–1365. 85 indexed citations

Tarzia, Giorgio, Andrea Duranti, Andrea Tontini, et al.. (2007). Identification of a Bioactive Impurity in a Commercial Sample of 6‐Methyl‐2‐p‐Tolylaminobenzo[d][1,3]Oxazin‐4‐One (URB754). Annali di Chimica. 97(9). 887–894. 20 indexed citations

Sanna, Pietro Paolo, et al.. (2005). Gene profiling of laser-microdissected brain regions and sub-regions. Brain Research Protocols. 15(2). 66–74. 14 indexed citations

Cammalleri, Maurizio, Robert Lütjens, Fulvia Berton, et al.. (2003). Time-restricted role for dendritic activation of the mTOR-p70 ^S6K pathway in the induction of late-phase long-term potentiation in the CA1. Proceedings of the National Academy of Sciences. 100(24). 14368–14373. 245 indexed citations

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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