Dai Horiuchi

2.9k total citations · 1 hit paper
22 papers, 1.8k citations indexed

About

Dai Horiuchi is a scholar working on Molecular Biology, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Dai Horiuchi has authored 22 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 11 papers in Oncology and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Dai Horiuchi's work include Microtubule and mitosis dynamics (5 papers), Ubiquitin and proteasome pathways (5 papers) and Cancer-related Molecular Pathways (5 papers). Dai Horiuchi is often cited by papers focused on Microtubule and mitosis dynamics (5 papers), Ubiquitin and proteasome pathways (5 papers) and Cancer-related Molecular Pathways (5 papers). Dai Horiuchi collaborates with scholars based in United States, Japan and Austria. Dai Horiuchi's co-authors include William M. Saxton, Curtis M. Lively, Andrei Goga, Noelle E. Huskey, Barry J. Dickson, Leonard Kusdra, Paul Yaswen, Alexey V. Bazarov, Pavan Bhat and Aaron DiAntonio and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Medicine.

In The Last Decade

Dai Horiuchi

21 papers receiving 1.8k citations

Hit Papers

Kinesin-1 and Dynein Are the Primary Motors for Fast Tran... 2006 2026 2012 2019 2006 100 200 300 400 500

Peers

Dai Horiuchi
Dai Horiuchi
Citations per year, relative to Dai Horiuchi Dai Horiuchi (= 1×) peers Nobuhiko Yokoyama

Countries citing papers authored by Dai Horiuchi

Since Specialization
Citations

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

Fields of papers citing papers by Dai Horiuchi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dai Horiuchi

This figure shows the co-authorship network connecting the top 25 collaborators of Dai Horiuchi. A scholar is included among the top collaborators of Dai Horiuchi 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 Dai Horiuchi. Dai Horiuchi 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.
Maruyama, Kosçak, Dai Horiuchi, Shunichi Sato, et al.. (2025). Impact of Storage Conditions on Bronchoalveolar Lavage Fluid Analysis. American Journal of Respiratory and Critical Care Medicine. 211(Supplement_1). A1714–A1714.
2.
Ζαννίκου, Μαρκέλλα, Deepak Kanojia, Sara F. Dunne, et al.. (2024). S100A8/A9 predicts response to PIM kinase and PD-1/PD-L1 inhibition in triple-negative breast cancer mouse models. SHILAP Revista de lepidopterología. 4(1). 22–22. 2 indexed citations
3.
Abe, Mitsuhiro, et al.. (2023). A retrospective comparison between digital to conventional drainage systems for secondary spontaneous pneumothorax related to diffuse interstitial lung disease. The Clinical Respiratory Journal. 17(8). 733–739. 1 indexed citations
4.
Kunder, Ratika, Sara F. Dunne, Byoung-Kyu Cho, et al.. (2021). Synergistic PIM kinase and proteasome inhibition as a therapeutic strategy for MYC-overexpressing triple-negative breast cancer. Cell chemical biology. 29(3). 358–372.e5. 14 indexed citations
5.
Callmann, Cassandra E., Lisa E. Cole, Caroline D. Kusmierz, et al.. (2020). Tumor cell lysate-loaded immunostimulatory spherical nucleic acids as therapeutics for triple-negative breast cancer. Proceedings of the National Academy of Sciences. 117(30). 17543–17550. 87 indexed citations
6.
Song, Ha Yong, Mohamed A. Ahmed, Yang Guo, et al.. (2018). NQO1 regulates mitotic progression and response to mitotic stress through modulating SIRT2 activity. Free Radical Biology and Medicine. 126. 358–371. 10 indexed citations
7.
Eckerdt, Frank, et al.. (2018). Antineoplastic effects of selective CDK9 inhibition with atuveciclib on cancer stem-like cells in triple-negative breast cancer. Oncotarget. 9(99). 37305–37318. 22 indexed citations
8.
Horiuchi, Dai, Roman Camarda, Alicia Y. Zhou, et al.. (2016). PIM1 kinase inhibition as a targeted therapy against triple-negative breast tumors with elevated MYC expression. Nature Medicine. 22(11). 1321–1329. 122 indexed citations
9.
Horiuchi, Dai, Brittany Anderton, & Andrei Goga. (2014). Taking on Challenging Targets: Making MYC Druggable. American Society of Clinical Oncology Educational Book. e497–e502. 49 indexed citations
10.
Horiuchi, Dai, Noelle E. Huskey, Leonard Kusdra, et al.. (2012). Chemical-genetic analysis of cyclin dependent kinase 2 function reveals an important role in cellular transformation by multiple oncogenic pathways. Proceedings of the National Academy of Sciences. 109(17). E1019–27. 64 indexed citations
11.
Horiuchi, Dai, Leonard Kusdra, Noelle E. Huskey, et al.. (2012). MYC pathway activation in triple-negative breast cancer is synthetic lethal with CDK inhibition. The Journal of Experimental Medicine. 209(4). 679–696. 265 indexed citations
12.
Horiuchi, Dai, Leonard Kusdra, Noelle E. Huskey, et al.. (2012). MYC pathway activation in triple-negative breast cancer is synthetic lethal with CDK inhibition. The Journal of Cell Biology. 197(1). i1–i1. 4 indexed citations
13.
Merrick, Karl A., Lara Wohlbold, Chao Zhang, et al.. (2011). Switching Cdk2 On or Off with Small Molecules to Reveal Requirements in Human Cell Proliferation. Molecular Cell. 42(5). 624–636. 69 indexed citations
14.
Wu, Fangting, Gabriel B. Loeb, Ruby Hsu, et al.. (2009). Up-regulation of miR-21 by HER2/neu Signaling Promotes Cell Invasion. Journal of Biological Chemistry. 284(27). 18515–18524. 165 indexed citations
15.
Horiuchi, Dai, et al.. (2007). Identification of an Axonal Kinesin-3 Motor for Fast Anterograde Vesicle Transport that Facilitates Retrograde Transport of Neuropeptides. Molecular Biology of the Cell. 19(1). 274–283. 144 indexed citations
16.
Horiuchi, Dai, et al.. (2007). Control of a Kinesin-Cargo Linkage Mechanism by JNK Pathway Kinases. Current Biology. 17(15). 1313–1317. 129 indexed citations
17.
Horiuchi, Dai, et al.. (2006). Kinesin-1 and Dynein Are the Primary Motors for Fast Transport of Mitochondria in Drosophila Motor Axons. Molecular Biology of the Cell. 17(4). 2057–2068. 538 indexed citations breakdown →
18.
Horiuchi, Dai, et al.. (2005). APLIP1, a Kinesin Binding JIP-1/JNK Scaffold Protein, Influences the Axonal Transport of Both Vesicles and Mitochondria in Drosophila. Current Biology. 15(23). 2137–2141. 110 indexed citations
19.
Sato, Kenichi, Miwa Kimoto, Dai Horiuchi, et al.. (2000). Adaptor protein Shc undergoes translocation and mediates up‐regulation of the tyrosine kinase c‐Src in EGF‐stimulated A431 cells. Genes to Cells. 5(9). 749–764. 43 indexed citations
20.
Tanaka, Youichi, et al.. (1989). [A case of renal cancer complicated with acute hypercalcemia and acute pancreatitis].. PubMed. 35(11). 1907–10. 1 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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