D. T. Johnson

1.5k total citations
70 papers, 1.1k citations indexed

About

D. T. Johnson is a scholar working on Molecular Biology, Insect Science and Plant Science. According to data from OpenAlex, D. T. Johnson has authored 70 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 24 papers in Insect Science and 14 papers in Plant Science. Recurrent topics in D. T. Johnson's work include Insect-Plant Interactions and Control (17 papers), Insect Pest Control Strategies (8 papers) and Cancer-related gene regulation (8 papers). D. T. Johnson is often cited by papers focused on Insect-Plant Interactions and Control (17 papers), Insect Pest Control Strategies (8 papers) and Cancer-related gene regulation (8 papers). D. T. Johnson collaborates with scholars based in United States, Netherlands and Japan. D. T. Johnson's co-authors include Zijie Sun, Richard Luong, Suk Hyung Lee, Raymond J. Grill, Pramod K. Dash, Anthony N. Moore, Gerald R. Cunha, Chunfang Zhu, Richard L. Kirkeeide and Nils P. Johnson and has published in prestigious journals such as Science, Journal of Biological Chemistry and Blood.

In The Last Decade

D. T. Johnson

66 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
D. T. Johnson United States 19 419 262 170 125 118 70 1.1k
Róbert Farkas Slovakia 18 490 1.2× 111 0.4× 104 0.6× 118 0.9× 67 0.6× 83 1.2k
J.G. Baust United States 20 218 0.5× 223 0.9× 158 0.9× 162 1.3× 83 0.7× 42 1.4k
Cédric Broussard France 24 399 1.0× 92 0.4× 308 1.8× 95 0.8× 31 0.3× 61 1.5k
Shu Fang China 24 691 1.6× 167 0.6× 87 0.5× 66 0.5× 234 2.0× 91 1.9k
Hitoshi Inoue Japan 19 303 0.7× 73 0.3× 469 2.8× 302 2.4× 128 1.1× 166 1.4k
Toshihiko Nakamura Japan 15 230 0.5× 55 0.2× 272 1.6× 191 1.5× 69 0.6× 78 920
Xiaoman Zhang China 16 388 0.9× 82 0.3× 98 0.6× 31 0.2× 110 0.9× 72 1.0k
Qi Yin China 22 1.1k 2.7× 49 0.2× 96 0.6× 112 0.9× 237 2.0× 61 1.8k
Kiyoshi Ishida Japan 22 300 0.7× 41 0.2× 227 1.3× 66 0.5× 197 1.7× 76 1.3k
J. W. Kuiper Netherlands 23 555 1.3× 37 0.1× 120 0.7× 144 1.2× 22 0.2× 48 1.6k

Countries citing papers authored by D. T. Johnson

Since Specialization
Citations

This map shows the geographic impact of D. T. Johnson'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 D. T. Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. T. Johnson more than expected).

Fields of papers citing papers by D. T. Johnson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. T. Johnson. 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 D. T. Johnson. The network helps show where D. T. Johnson may publish in the future.

Co-authorship network of co-authors of D. T. Johnson

This figure shows the co-authorship network connecting the top 25 collaborators of D. T. Johnson. A scholar is included among the top collaborators of D. T. Johnson 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 D. T. Johnson. D. T. Johnson 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.
Johnson, Nils P., Rik Adrichem, Nikolaos Kakouros, et al.. (2026). Clinical outcomes and haemodynamic response after blinded stress assessment of moderate aortic stenosis. EuroIntervention. 22(6). e347–e357.
2.
Johnson, D. T., Dinghai Zheng, Ruijia Wang, et al.. (2021). Alternative polyadenylation dysregulation contributes to the differentiation block of acute myeloid leukemia. Blood. 139(3). 424–438. 15 indexed citations
3.
Johnson, D. T., Jiarong Zhou, Ashley V. Kroll, et al.. (2021). Acute myeloid leukemia cell membrane-coated nanoparticles for cancer vaccination immunotherapy. Leukemia. 36(4). 994–1005. 64 indexed citations
4.
Zimmermann, Frederik M., Thomas P. Mast, Nils P. Johnson, et al.. (2021). Deep learning for prediction of fractional flow reserve from resting coronary pressure curves. EuroIntervention. 17(1). 51–58. 3 indexed citations
5.
Stoner, Samuel A., Ming Yan, Katherine Liu, et al.. (2019). Hippo kinase loss contributes to del(20q) hematologic malignancies through chronic innate immune activation. Blood. 134(20). 1730–1744. 12 indexed citations
6.
He, Yongfeng, D. T. Johnson, Julie Yang, et al.. (2019). Loss of the tumor suppressor, Tp53, enhances the androgen receptor-mediated oncogenic transformation and tumor development in the mouse prostate. Oncogene. 38(38). 6507–6520. 8 indexed citations
7.
Palmer, Nathan, D. T. Johnson, Sarah J. Medina, et al.. (2018). Destabilizing mutations encode nongenetic variation that drives evolutionary innovation. Science. 359(6383). 1542–1545. 35 indexed citations
8.
Maddamsetti, Rohan, et al.. (2018). Gain‐of‐function experiments with bacteriophage lambda uncover residues under diversifying selection in nature. Evolution. 72(10). 2234–2243. 12 indexed citations
9.
Shima, Takahiro, Sayuri Miyauchi, D. T. Johnson, et al.. (2017). CPSF1 Regulates AML1-ETO Fusion Gene Polyadenylation and Stability in t(8;21) Acute Myelogenous Leukemia. Blood. 130. 2498–2498. 2 indexed citations
10.
Johnson, D. T., et al.. (2017). Characterization of the Post-Transcriptional Regulation of AML1-ETO Expression in t(8;21) Leukemia Cells. Blood. 130. 3790–3790. 1 indexed citations
11.
Johnson, D. T., Erika Hooker, Richard Luong, et al.. (2016). Conditional Expression of the Androgen Receptor Increases Susceptibility of Bladder Cancer in Mice. PLoS ONE. 11(2). e0148851–e0148851. 24 indexed citations
12.
Lee, Seon Hwa, Richard Luong, D. T. Johnson, et al.. (2015). Androgen signaling is a confounding factor for β-catenin-mediated prostate tumorigenesis. Oncogene. 35(6). 702–714. 27 indexed citations
13.
Lee, Suk Hyung, D. T. Johnson, Richard Luong, & Zijie Sun. (2014). Crosstalking between Androgen and PI3K/AKT Signaling Pathways in Prostate Cancer Cells. Journal of Biological Chemistry. 290(5). 2759–2768. 76 indexed citations
14.
Johnson, D. T., Richard Luong, Suk Hyung Lee, et al.. (2012). Deletion of Leucine Zipper Tumor Suppressor 2 (Lzts2) Increases Susceptibility to Tumor Development. Journal of Biological Chemistry. 288(6). 3727–3738. 18 indexed citations
15.
Zhu, Chunfang, Richard Luong, Ming Zhuo, et al.. (2011). Conditional Expression of the Androgen Receptor Induces Oncogenic Transformation of the Mouse Prostate. Journal of Biological Chemistry. 286(38). 33478–33488. 38 indexed citations
16.
Johnson, D. T., et al.. (2010). Differences in Defoliation of Fruit Genotypes byAdult Japanese Beetle Feeding. Journal of American Pomological Society. 64(4). 184–198. 2 indexed citations
17.
Yang, Michael G., George P. Luke, William C. Shakespeare, et al.. (2001). A novel phosphotyrosine mimetic 4′-carboxymethyloxy-3′-phosphonophenylalanine (cpp): exploitation in the design of nonpeptide inhibitors of pp60Src SH2 domain. Bioorganic & Medicinal Chemistry Letters. 11(17). 2319–2323. 16 indexed citations
18.
Johnson, D. T., et al.. (1998). Development of an IPM monitoring program for rice water weevil adults.. 95–102. 1 indexed citations
19.
Johnson, D. T. & Rafael Bahamonde. (1995). EFFECTS OF GENDER AND THE LEWIS FORMULA IN MECHANICAL POWER ESTIMATES. ISBS - Conference Proceedings Archive. 1(1).
20.
Johnson, D. T.. (1994). Understanding air-gun bubble behavior. Geophysics. 59(11). 1729–1734. 29 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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