David P. Davis

2.9k total citations
29 papers, 1.5k citations indexed

About

David P. Davis is a scholar working on Molecular Biology, Cell Biology and Plant Science. According to data from OpenAlex, David P. Davis has authored 29 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 7 papers in Cell Biology and 5 papers in Plant Science. Recurrent topics in David P. Davis's work include Microtubule and mitosis dynamics (4 papers), Dermatological diseases and infestations (4 papers) and Peanut Plant Research Studies (4 papers). David P. Davis is often cited by papers focused on Microtubule and mitosis dynamics (4 papers), Dermatological diseases and infestations (4 papers) and Peanut Plant Research Studies (4 papers). David P. Davis collaborates with scholars based in United States, France and Czechia. David P. Davis's co-authors include Daniel C. Gray, Klaus P. Hoeflich, Lesley Murray, Deborah L. Segaloff, Janet Tien, Howard M. Stern, Somasekar Seshagiri, Roger D. Moon, Yair Argon and Fred J. Stevens and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and The Journal of Cell Biology.

In The Last Decade

David P. Davis

29 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David P. Davis United States 18 1.1k 257 254 234 121 29 1.5k
Heike Laman United Kingdom 21 946 0.9× 398 1.5× 344 1.4× 209 0.9× 158 1.3× 36 1.4k
June‐Tai Wu Taiwan 18 1.4k 1.3× 160 0.6× 369 1.5× 154 0.7× 145 1.2× 42 1.8k
Koji Sagane Japan 19 1.2k 1.2× 249 1.0× 250 1.0× 207 0.9× 144 1.2× 27 1.9k
Yosuke Matsuoka Japan 17 1.3k 1.2× 147 0.6× 129 0.5× 188 0.8× 96 0.8× 27 1.7k
Matthew J. Schibler United States 13 1.3k 1.2× 100 0.4× 351 1.4× 394 1.7× 165 1.4× 17 1.6k
Nicholas R. Helps United Kingdom 14 1.4k 1.4× 129 0.5× 190 0.7× 448 1.9× 95 0.8× 15 1.7k
Svetlana Lyapina United States 9 1.9k 1.8× 286 1.1× 474 1.9× 445 1.9× 147 1.2× 13 2.1k
Louis P. Deiss United States 14 1.2k 1.1× 435 1.7× 315 1.2× 216 0.9× 178 1.5× 17 1.8k
Wade Edris United States 17 1.0k 1.0× 311 1.2× 236 0.9× 128 0.5× 114 0.9× 31 1.5k
Eric S. Witze United States 17 1.4k 1.3× 132 0.5× 277 1.1× 325 1.4× 75 0.6× 25 1.8k

Countries citing papers authored by David P. Davis

Since Specialization
Citations

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

Fields of papers citing papers by David P. Davis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David P. Davis

This figure shows the co-authorship network connecting the top 25 collaborators of David P. Davis. A scholar is included among the top collaborators of David P. Davis 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 P. Davis. David P. Davis 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.
Torres, Jorge Z., Matthew K. Summers, David Peterson, et al.. (2011). The STARD9/Kif16a Kinesin Associates with Mitotic Microtubules and Regulates Spindle Pole Assembly. Cell. 147(6). 1309–1323. 62 indexed citations
2.
Peterson, David, James Lee, William F. Forrest, et al.. (2010). A Chemosensitization Screen Identifies TP53RK, a Kinase that Restrains Apoptosis after Mitotic Stress. Cancer Research. 70(15). 6325–6335. 26 indexed citations
3.
Li, Li, Kangyu Zhang, James Lee, et al.. (2009). Discovering cancer genes by integrating network and functional properties. BMC Medical Genomics. 2(1). 61–61. 40 indexed citations
4.
Jaiswal, Bijay S., Vasantharajan Janakiraman, Noelyn M. Kljavin, et al.. (2009). Combined Targeting of BRAF and CRAF or BRAF and PI3K Effector Pathways Is Required for Efficacy in NRAS Mutant Tumors. PLoS ONE. 4(5). e5717–e5717. 85 indexed citations
5.
Hoeflich, Klaus P., Bijay S. Jaiswal, David P. Davis, & Somasekar Seshagiri. (2008). Inducible BRAF Suppression Models for Melanoma Tumorigenesis. Methods in enzymology on CD-ROM/Methods in enzymology. 439. 25–38. 8 indexed citations
6.
Evangelista, Marie, James Lee, Leon Parker, et al.. (2008). Kinome siRNA Screen Identifies Regulators of Ciliogenesis and Hedgehog Signal Transduction. Science Signaling. 1(39). ra7–ra7. 64 indexed citations
7.
Evangelista, Marie, James Lee, Leon Parker, et al.. (2008). Supplementary Materials for Kinome siRNA Screen Identifies Regulators of Ciliogenesis and Hedgehog Signal Transduction. 13 indexed citations
8.
Hoeflich, Klaus P., Daniel C. Gray, Michael Eby, et al.. (2006). Oncogenic BRAF Is Required for Tumor Growth and Maintenance in Melanoma Models. Cancer Research. 66(2). 999–1006. 185 indexed citations
9.
Gray, Daniel C., Adrian M. Jubb, Deborah Hogue, et al.. (2005). Maternal Embryonic Leucine Zipper Kinase/Murine Protein Serine-Threonine Kinase 38 Is a Promising Therapeutic Target for Multiple Cancers. Cancer Research. 65(21). 9751–9761. 149 indexed citations
10.
Davis, David P. & Deborah L. Segaloff. (2002). N-linked carbohydrates on G protein-coupled receptors: Mapping sites of attachment and determining functional roles. Methods in enzymology on CD-ROM/Methods in enzymology. 343. 200–212. 6 indexed citations
11.
Davis, David P., Gloria Gallo, Shawn M. Vogen, et al.. (2001). Both the environment and somatic mutations govern the aggregation pathway of pathogenic immunoglobulin light chain 1 1Edited by A. Fersht. Journal of Molecular Biology. 313(5). 1021–1034. 49 indexed citations
12.
Davis, David P., Rosemarie Raffen, Shawn M. Vogen, et al.. (2000). Inhibition of Amyloid Fiber Assembly by Both BiP and Its Target Peptide. Immunity. 13(4). 433–442. 33 indexed citations
13.
Davis, David P., R. Khurana, Stephen C. Meredith, Fred J. Stevens, & Yair Argon. (1999). Mapping the Major Interaction Between Binding Protein and Ig Light Chains to Sites Within the Variable Domain. The Journal of Immunology. 163(7). 3842–3850. 24 indexed citations
14.
Davis, David P., et al.. (1998). Association of Gonadotropin Receptor Precursors with the Protein Folding Chaperone Calnexin1. Endocrinology. 139(4). 1588–1593. 57 indexed citations
15.
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17.
Davis, David P. & Roger D. Moon. (1990). Dynamics of Swine Mange: A Critical Review of the Literature. Journal of Medical Entomology. 27(5). 727–737. 39 indexed citations
18.
Davis, David P. & Roger D. Moon. (1990). Density, Location, and Sampling of Sarcoptes scabiei (Acari: Sarcoptidae) on Experimentally Infested Pigs. Journal of Medical Entomology. 27(3). 391–398. 10 indexed citations
19.
Davis, David P. & Roger D. Moon. (1987). Survival of Sarcoptes scabiei (De Geer) Stored in Three Media at Three Temperatures. Journal of Parasitology. 73(3). 661–661. 9 indexed citations
20.
Davis, David P. & Ralph E. Williams. (1986). Influence of hog lice, Haematopinus suis, on blood components, behavior, weight gain and feed efficiency of pigs. Veterinary Parasitology. 22(3-4). 307–314. 13 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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