David A. Carlson

5.4k total citations
153 papers, 4.3k citations indexed

About

David A. Carlson is a scholar working on Insect Science, Molecular Biology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, David A. Carlson has authored 153 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Insect Science, 24 papers in Molecular Biology and 24 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in David A. Carlson's work include Insect and Pesticide Research (53 papers), Insect behavior and control techniques (29 papers) and Insect and Arachnid Ecology and Behavior (21 papers). David A. Carlson is often cited by papers focused on Insect and Pesticide Research (53 papers), Insect behavior and control techniques (29 papers) and Insect and Arachnid Ecology and Behavior (21 papers). David A. Carlson collaborates with scholars based in United States, Canada and United Kingdom. David A. Carlson's co-authors include Tack‐Don Han, Ulrich R. Bernier, Bruce D. Sutton, Dov Borovsky, Morton Beroza, Daniel L. Kline, M. S. Mayer, Donald L. Silhacek, Jennifer James and Dennis R. Nelson and has published in prestigious journals such as Science, Journal of Biological Chemistry and Analytical Chemistry.

In The Last Decade

David A. Carlson

148 papers receiving 4.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David A. Carlson United States 34 1.9k 1.1k 927 906 741 153 4.3k
Jonathan D. Moore United Kingdom 42 552 0.3× 737 0.7× 438 0.5× 3.1k 3.4× 259 0.3× 117 5.9k
Hans‐Michael Müller Germany 44 1.1k 0.6× 240 0.2× 131 0.1× 2.7k 2.9× 454 0.6× 156 6.1k
James A. Svoboda United States 31 1.5k 0.8× 618 0.6× 460 0.5× 771 0.9× 1.3k 1.7× 129 2.9k
Alan L. Harvey United Kingdom 44 457 0.2× 2.3k 2.0× 92 0.1× 4.9k 5.4× 958 1.3× 195 7.6k
Anthony D. Long United States 43 610 0.3× 4.3k 3.9× 966 1.0× 3.9k 4.3× 536 0.7× 114 8.5k
Dmitry Kuznetsov Russia 24 225 0.1× 510 0.5× 221 0.2× 2.3k 2.5× 204 0.3× 73 3.8k
Ralph A. Dean United States 58 464 0.2× 630 0.6× 814 0.9× 7.4k 8.2× 406 0.5× 175 14.8k
Jaap Heringa Netherlands 12 152 0.1× 837 0.8× 210 0.2× 4.3k 4.8× 220 0.3× 29 6.1k
Olof Emanuelsson Sweden 23 320 0.2× 540 0.5× 263 0.3× 8.3k 9.2× 274 0.4× 33 10.8k
Shengqiang Shu United States 27 640 0.3× 1.6k 1.4× 747 0.8× 5.5k 6.0× 378 0.5× 57 9.0k

Countries citing papers authored by David A. Carlson

Since Specialization
Citations

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

Fields of papers citing papers by David A. Carlson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David A. Carlson. 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 David A. Carlson. The network helps show where David A. Carlson may publish in the future.

Co-authorship network of co-authors of David A. Carlson

This figure shows the co-authorship network connecting the top 25 collaborators of David A. Carlson. A scholar is included among the top collaborators of David A. Carlson 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 David A. Carlson. David A. Carlson 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.
Carlson, David A., et al.. (2023). Death‐associated protein kinase 3 regulates the myogenic reactivity of cerebral arteries. Experimental Physiology. 108(7). 986–997. 4 indexed citations
2.
Hughes, Philip F., et al.. (2019). A highly selective inhibitor of interleukin-1 receptor–associated kinases 1/4 (IRAK-1/4) delineates the distinct signaling roles of IRAK-1/4 and the TAK1 kinase. Journal of Biological Chemistry. 295(6). 1565–1574. 19 indexed citations
3.
Eibschutz, Liesl S., Juliane Totzke, Jose Roques, et al.. (2018). Genetic and pharmacological validation of TAK1 inhibition in macrophages as a therapeutic strategy to effectively inhibit TNF secretion. Scientific Reports. 8(1). 17058–17058. 26 indexed citations
4.
Bellaye, Pierre‐Simon, Chiko Shimbori, Toyoshi Yanagihara, et al.. (2018). Synergistic role of HSP90α and HSP90β to promote myofibroblast persistence in lung fibrosis. European Respiratory Journal. 51(2). 1700386–1700386. 44 indexed citations
5.
Carlson, David A., Cindy Sutherland, Clara Redondo, et al.. (2018). Targeting Pim Kinases and DAPK3 to Control Hypertension. Cell chemical biology. 25(10). 1195–1207.e32. 17 indexed citations
6.
Mihok, Steve & David A. Carlson. (2007). Performance of Painted Plywood and Cloth Nzi Traps Relative to Manitoba and Greenhead Traps for Tabanids and Stable Flies. Journal of Economic Entomology. 100(2). 613–618. 11 indexed citations
7.
Mihok, Steve, David A. Carlson, & Paul N. Ndegwa. (2007). Tsetse and other biting fly responses to Nzi traps baited with octenol, phenols and acetone. Medical and Veterinary Entomology. 21(1). 70–84. 40 indexed citations
8.
Katritzky, Alan R., Dimitar A. Dobchev, Indrek Tulp, Mati Karelson, & David A. Carlson. (2006). QSAR study of mosquito repellents using Codessa Pro. Bioorganic & Medicinal Chemistry Letters. 16(8). 2306–2311. 44 indexed citations
9.
Carlson, David A.. (2002). Free-Swinging Attention. The Psychoanalytic Quarterly. 71(4). 725–750. 6 indexed citations
10.
Hogsette, Jerome A., et al.. (2002). Development of Granular Boric Acid Sugar Baits for House Flies (Diptera: Muscidae). Journal of Economic Entomology. 95(5). 1110–1112. 9 indexed citations
11.
Carlson, David A.. (1998). Rules and Web—object systems. 8(4). 16–17. 1 indexed citations
12.
Carlson, David A. & Sudha Ram. (1996). Modeling organizations as a social network of distributed knowledge-based systems. IEEE Computer Society Press eBooks. 162–171. 1 indexed citations
13.
Manns, Mary Lynn & David A. Carlson. (1992). Retraining procedural programmers. 131–133.
14.
Carlson, David A. & John M. Conroy. (1988). The fast fourier transform and sparse matrix computations: a study of two applications on teh HORIZON supercomputer. Conference on High Performance Computing (Supercomputing). 55–58. 1 indexed citations
15.
Carlson, David A.. (1986). Time-space tradeoffs for tree search and traversal. 585–594. 1 indexed citations
16.
Carlson, David A.. (1985). Performing Tree and Prefix Computations on Modified Mesh-Connected Parallel Computers.. Proceedings of the International Conference on Parallel Processing. 715–718. 9 indexed citations
17.
Antony, C., Terry L. Davis, David A. Carlson, J.M. Pechine, & J.M. Jallon. (1985). Compared behavioral responses of maleDrosophila melanogaster (Canton S) to natural and synthetic aphrodisiacs. Journal of Chemical Ecology. 11(12). 1617–1629. 161 indexed citations
18.
Carlson, David A.. (1984). Parallel Processing of Tree-like Computations.. International Conference on Distributed Computing Systems. 192–200. 6 indexed citations
19.
Carlson, David A. & John E. Savage. (1983). Size-Space Tradeoffs for Oblivious Computations. Journal of Computer and System Sciences. 26(1). 65–81. 1 indexed citations
20.
Carlson, David A.. (1975). Good sequences of integers. Journal of Number Theory. 7(1). 91–104. 3 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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