Kim Kaiser

4.3k total citations
51 papers, 3.5k citations indexed

About

Kim Kaiser is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Genetics. According to data from OpenAlex, Kim Kaiser has authored 51 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 18 papers in Cellular and Molecular Neuroscience and 14 papers in Genetics. Recurrent topics in Kim Kaiser's work include Neurobiology and Insect Physiology Research (18 papers), RNA and protein synthesis mechanisms (8 papers) and Genomics and Chromatin Dynamics (8 papers). Kim Kaiser is often cited by papers focused on Neurobiology and Insect Physiology Research (18 papers), RNA and protein synthesis mechanisms (8 papers) and Genomics and Chromatin Dynamics (8 papers). Kim Kaiser collaborates with scholars based in United Kingdom, United States and Germany. Kim Kaiser's co-authors include J. Douglas Armstrong, Mingyao Yang, Julian A. T. Dow, Zongsheng Wang, Noreen E. Murray, Mehmet A. Sözen, Tim Tully, Shireen A. Davies, Michael Forte and John B. Connolly and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Kim Kaiser

50 papers receiving 3.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kim Kaiser United Kingdom 26 2.2k 1.7k 976 554 502 51 3.5k
Michael J. Pankratz Germany 32 1.5k 0.7× 1.6k 0.9× 791 0.8× 315 0.6× 458 0.9× 59 3.3k
Shireen A. Davies United Kingdom 34 2.0k 0.9× 1.7k 1.0× 726 0.7× 763 1.4× 690 1.4× 61 3.9k
Toshihiro Kitamoto United States 31 3.2k 1.5× 1.1k 0.6× 1.3k 1.3× 427 0.8× 445 0.9× 74 4.0k
Henrike Scholz Germany 23 2.3k 1.1× 1.1k 0.7× 1.0k 1.1× 366 0.7× 333 0.7× 41 3.3k
Serge Birman France 31 2.8k 1.3× 1.1k 0.6× 1.2k 1.2× 311 0.6× 290 0.6× 67 3.8k
Tomoatsu Ikeya Switzerland 9 1.6k 0.7× 897 0.5× 500 0.5× 360 0.6× 560 1.1× 9 2.7k
Africa Couto United Kingdom 8 1.9k 0.9× 1.4k 0.9× 765 0.8× 151 0.3× 517 1.0× 9 3.1k
Maria Monastirioti Greece 18 2.2k 1.0× 594 0.4× 1.2k 1.3× 337 0.6× 320 0.6× 24 2.9k
Ryusuke Niwa Japan 37 2.3k 1.1× 2.0k 1.2× 1.0k 1.0× 298 0.5× 583 1.2× 87 4.7k
William L. Pak United States 45 4.0k 1.8× 3.3k 2.0× 558 0.6× 258 0.5× 403 0.8× 98 5.7k

Countries citing papers authored by Kim Kaiser

Since Specialization
Citations

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

Fields of papers citing papers by Kim Kaiser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kim Kaiser

This figure shows the co-authorship network connecting the top 25 collaborators of Kim Kaiser. A scholar is included among the top collaborators of Kim Kaiser 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 Kaiser. Kim Kaiser 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.
Kaiser, Kim, et al.. (2022). Electromagnetic Design of Electrical Machines - New Potentials of Additive Manufacturing with the Example of the Transverse Flux Machine. 2022 International Conference on Electrical Machines (ICEM). 1491–1497. 2 indexed citations
2.
Kaiser, Kim, et al.. (2021). Cannabinoid Hyperemesis Syndrome in an Athlete. The Journal of the American Board of Family Medicine. 34(4). 811–813. 2 indexed citations
3.
Rosay, Philippe, J. Douglas Armstrong, Zhong‐Sheng Wang, & Kim Kaiser. (2001). Synchronized Neural Activity in the Drosophila Memory Centers and Its Modulation by amnesiac. Neuron. 30(3). 759–770. 55 indexed citations
4.
Waddell, Scott, J. Douglas Armstrong, Toshihiro Kitamoto, Kim Kaiser, & William G. Quinn. (2000). The amnesiac Gene Product Is Expressed in Two Neurons in the Drosophila Brain that Are Critical for Memory. Cell. 103(5). 805–813. 254 indexed citations
5.
An, Xin, J. Douglas Armstrong, Kim Kaiser, & Kevin M.C. O’Dell. (2000). The Effects of EctopicWhiteandTransformerExpression onDrosophilaCourtship Behavior. Journal of Neurogenetics. 14(4). 227–243. 14 indexed citations
6.
O’Dell, Kevin M.C., David Jamieson, Stephen F. Goodwin, & Kim Kaiser. (1999). Abnormal Courtship Conditioning in Males Mutant for the RI Regulatory Subunit ofDrosophilaProtein Kinase A. Journal of Neurogenetics. 13(1-2). 105–118. 13 indexed citations
7.
Armstrong, J. Douglas, J. Steven de Belle, Zongsheng Wang, & Kim Kaiser. (1998). Metamorphosis of the Mushroom Bodies; Large-Scale Rearrangements of the Neural Substrates for Associative Learning and Memory in Drosophila. Learning & Memory. 5(1). 102–114. 126 indexed citations
8.
O’Dell, Kevin M.C. & Kim Kaiser. (1997). Sexual behaviour: Secrets and flies. Current Biology. 7(6). R345–R347. 7 indexed citations
9.
10.
Korneev, Sergei A., S. E. Blackshaw, Kim Kaiser, & Jane A. Davies. (1996). cDNA libraries from identified neurons. Proceedings of the Royal Society B Biological Sciences. 263(1366). 57–62. 11 indexed citations
11.
Kaiser, Kim, et al.. (1996). The Drosophila melanogaster gene vha14 encoding a 14-kDa F-subunit of the vacuolar ATPase. Gene. 172(2). 239–243. 9 indexed citations
12.
Wang, Zongsheng, et al.. (1996). Characterisation of vha26, the Drosophila gene for a 26 kDa E-subunit of the vacuolar ATPase. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1283(1). 4–9. 11 indexed citations
13.
Davies, Shireen A., Stephen F. Goodwin, D. C. Kelly, et al.. (1996). Analysis and Inactivation of vha55, the Gene Encoding the Vacuolar ATPase B-subunit in Drosophila melanogaster Reveals a Larval Lethal Phenotype. Journal of Biological Chemistry. 271(48). 30677–30684. 101 indexed citations
14.
O’Dell, Kevin M.C., J. Douglas Armstrong, Mingyao Yang, & Kim Kaiser. (1995). Functional dissection of the drosophila mushroom bodies by selective feminization ofagenetically defined subcompartments. Neuron. 15(1). 55–61. 122 indexed citations
15.
Jacobs, Howard T., et al.. (1995). Characterisation ofSaccharomyces cerevisiae genes encoding ribosomal protein YL6. Molecular and General Genetics MGG. 247(2). 247–254. 6 indexed citations
16.
Yang, Mingyao, J. Douglas Armstrong, Ilya Vilinsky, Nicholas J. Strausfeld, & Kim Kaiser. (1995). Subdivision of the drosophila mushroom bodies by enhancer-trap expression patterns. Neuron. 15(1). 45–54. 302 indexed citations
17.
Davies, R. Wayne, A. Roberts, Gareth Griffith, et al.. (1994). Enhanced Access to Rare Brain cDNAs by Prescreening Libraries: 207 New Mouse Brain ESTs. Genomics. 24(3). 456–463. 11 indexed citations
18.
Kaiser, Kim. (1993). Second generation enhancer traps. Current Biology. 3(8). 560–562. 17 indexed citations
19.
Sentry, John W. & Kim Kaiser. (1992). P element transposition and targeted manipulation of the Drosophila genome. Trends in Genetics. 8(10). 329–331. 16 indexed citations
20.
Kaiser, Kim. (1990). What's new?: From gene to phenotype in Drosophila and other organisms. BioEssays. 12(6). 297–301. 10 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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