Gene C. Jamieson

1.5k total citations
32 papers, 1.2k citations indexed

About

Gene C. Jamieson is a scholar working on Molecular Biology, Spectroscopy and Cellular and Molecular Neuroscience. According to data from OpenAlex, Gene C. Jamieson has authored 32 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 8 papers in Spectroscopy and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Gene C. Jamieson's work include Neurobiology and Insect Physiology Research (5 papers), Analytical Chemistry and Chromatography (4 papers) and Cancer therapeutics and mechanisms (4 papers). Gene C. Jamieson is often cited by papers focused on Neurobiology and Insect Physiology Research (5 papers), Analytical Chemistry and Chromatography (4 papers) and Cancer therapeutics and mechanisms (4 papers). Gene C. Jamieson collaborates with scholars based in United States, United Kingdom and Netherlands. Gene C. Jamieson's co-authors include David A. Schooley, David Rhodes, Charles A. Miller, Robert M. Scarborough, Sven Krämer, Glenn McEnroe, Carol C. Reuter, Philip Haworth, Carl Djerassi and Robert D. Walkup and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Gene C. Jamieson

32 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gene C. Jamieson United States 18 390 321 318 242 207 32 1.2k
Masaaki Uchiyama Japan 20 444 1.1× 322 1.0× 162 0.5× 308 1.3× 116 0.6× 95 1.2k
Alexandra Z. Andreou Germany 15 831 2.1× 311 1.0× 179 0.6× 214 0.9× 74 0.4× 24 1.4k
Franz Suter Switzerland 26 1.3k 3.3× 155 0.5× 220 0.7× 49 0.2× 62 0.3× 45 1.6k
Shawn Doonan Ireland 25 1.3k 3.2× 133 0.4× 63 0.2× 109 0.5× 219 1.1× 103 2.0k
Masana Noma Japan 25 971 2.5× 690 2.1× 123 0.4× 64 0.3× 51 0.2× 61 2.1k
Masakazu Fukuta Japan 26 916 2.3× 409 1.3× 96 0.3× 100 0.4× 130 0.6× 46 1.6k
Steve Compton United States 4 456 1.2× 186 0.6× 45 0.1× 93 0.4× 41 0.2× 4 972
W H Habig United States 19 926 2.4× 394 1.2× 200 0.6× 58 0.2× 70 0.3× 25 2.0k
Zhiguang Yuchi China 20 803 2.1× 196 0.6× 115 0.4× 363 1.5× 32 0.2× 77 1.2k
Tomohide Uno Japan 15 473 1.2× 75 0.2× 124 0.4× 43 0.2× 183 0.9× 72 1.1k

Countries citing papers authored by Gene C. Jamieson

Since Specialization
Citations

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

Fields of papers citing papers by Gene C. Jamieson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gene C. Jamieson. 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 Gene C. Jamieson. The network helps show where Gene C. Jamieson may publish in the future.

Co-authorship network of co-authors of Gene C. Jamieson

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

All Works

20 of 20 papers shown
1.
Nijenhuis, Cynthia M., Hilde Rosing, Alwin D. R. Huitema, et al.. (2017). Metabolism and disposition of the anticancer quinolone derivative vosaroxin, a novel inhibitor of topoisomerase II. Investigational New Drugs. 35(4). 478–490. 3 indexed citations
2.
Nijenhuis, Cynthia M., Hilde Rosing, Gene C. Jamieson, et al.. (2016). Quantification of vosaroxin and its metabolites N-desmethylvosaroxin and O-desmethylvosaroxin in human plasma and urine using high-performance liquid chromatography-tandem mass spectrometry. Journal of Chromatography B. 1027. 1–10. 3 indexed citations
3.
Jamieson, Gene C., Judith A. Fox, Ming Poi, & Stephen A. Strickland. (2016). Molecular and Pharmacologic Properties of the Anticancer Quinolone Derivative Vosaroxin: A New Therapeutic Agent for Acute Myeloid Leukemia. Drugs. 76(13). 1245–1255. 27 indexed citations
4.
Binnerts, Minke E., Kevin L. Otipoby, Brian T. Hopkins, et al.. (2015). Abstract C186: SNS-062 is a potent noncovalent BTK inhibitor with comparable activity against wild type BTK and BTK with an acquired resistance mutation. Molecular Cancer Therapeutics. 14(12_Supplement_2). C186–C186. 22 indexed citations
5.
Cawthray, Jacqueline F., et al.. (2014). Iron(iii)-binding of the anticancer agents doxorubicin and vosaroxin. Dalton Transactions. 44(5). 2348–2358. 28 indexed citations
6.
Hvattum, Erlend, Per T. Normann, Gene C. Jamieson, Jan‐Ji Lai, & Tore Skotland. (1995). Detection and quantitation of gadolinium chelates in human serum and urine by high-performance liquid chromatography and post-column derivatization of gadolinium with Arsenazo III. Journal of Pharmaceutical and Biomedical Analysis. 13(7). 927–932. 26 indexed citations
7.
8.
Quistad, Gary B., et al.. (1990). Structure of paralytic acylpolyamines from the spider Agelenopsisaperta. Biochemical and Biophysical Research Communications. 169(1). 51–56. 49 indexed citations
9.
Gut, Josef, James R. Trudell, & Gene C. Jamieson. (1988). Leukotriene biosynthesis: Direct chemical ionization mass spectrometry of underivatized arachidonic acid metabolites. Journal of Mass Spectrometry. 15(9). 509–516. 6 indexed citations
10.
Gut, Josef, Gene C. Jamieson, & James R. Trudell. (1988). Direct Chemical Ionization Mass Spectrometry of Underivatized Arachidonic Acid Metabolites: Application to Leukotriene Biosynthesis. PubMed. 49. 185–189. 1 indexed citations
11.
Gut, Josef, Gene C. Jamieson, & James R. Trudell. (1987). Quantification of 5- and 15-HPETE's by direct chemical ionization mass spectrometry. Free Radical Biology and Medicine. 3(5). 323–328. 4 indexed citations
12.
Rhodes, David, et al.. (1987). Determination of Betaines by Fast Atom Bombardment Mass Spectrometry. PLANT PHYSIOLOGY. 84(3). 781–788. 73 indexed citations
13.
Rhodes, David, et al.. (1987). Amino Acid Metabolism of Lemna minor L.. PLANT PHYSIOLOGY. 84(3). 775–780. 81 indexed citations
14.
Baker, Fred C., et al.. (1985). Identification of the juvenile hormones from adult Attacus atlas. Insect Biochemistry. 15(3). 321–324. 5 indexed citations
15.
Hanson, Andrew D., et al.. (1985). Betaine synthesis in chenopods: Localization in chloroplasts. Proceedings of the National Academy of Sciences. 82(11). 3678–3682. 114 indexed citations
16.
Jamieson, Gene C., Carol C. Reuter, & William L. Fitch. (1985). Polyimide-coated fused silica as an extended probe for in-beam chemical ionization mass spectrometry. Analytical Chemistry. 57(1). 121–123. 7 indexed citations
17.
Quistad, Gary B., Luana E. Staiger, Gene C. Jamieson, & David A. Schooley. (1983). Fluvalinate metabolism by rats. Journal of Agricultural and Food Chemistry. 31(3). 589–596. 8 indexed citations
18.
Jamieson, Gene C.. (1982). Hydrogenation of olefins in a capillary GC/MS interface. Journal of High Resolution Chromatography. 5(11). 632–633. 7 indexed citations
19.
20.

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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