Yuki Ono

1.2k total citations · 1 hit paper
15 papers, 682 citations indexed

About

Yuki Ono is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Oncology. According to data from OpenAlex, Yuki Ono has authored 15 papers receiving a total of 682 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Cellular and Molecular Neuroscience and 4 papers in Oncology. Recurrent topics in Yuki Ono's work include Receptor Mechanisms and Signaling (5 papers), Protein Kinase Regulation and GTPase Signaling (4 papers) and Neuropeptides and Animal Physiology (3 papers). Yuki Ono is often cited by papers focused on Receptor Mechanisms and Signaling (5 papers), Protein Kinase Regulation and GTPase Signaling (4 papers) and Neuropeptides and Animal Physiology (3 papers). Yuki Ono collaborates with scholars based in Japan, United States and Germany. Yuki Ono's co-authors include Asuka Inoue, Junken Aoki, Kouki Kawakami, Satoru Ishida, Takayuki Kishi, Akiharu Uwamizu, Francois Marie Ngako Kadji, Nadia Arang, Yuji Shinjo and Francesco Raimondi and has published in prestigious journals such as Cell, Nature Communications and The Journal of Experimental Medicine.

In The Last Decade

Yuki Ono

14 papers receiving 679 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Illuminating G-Protein-Coupling Selectivity of GPCRs

2019 396 citations Asuka Inoue, Francesco Raimondi et al. Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yuki Ono Japan	8	544	238	68	62	57	15	682
Chanjuan Xu China	16	509 0.9×	331 1.4×	58 0.9×	18 0.3×	29 0.5×	28	704
Darlaine Pétrin Canada	15	432 0.8×	218 0.9×	55 0.8×	16 0.3×	76 1.3×	30	586
Jurgen F.M. Vanhauwe Belgium	8	596 1.1×	302 1.3×	38 0.6×	53 0.9×	40 0.7×	10	791
Nikoleta G. Tsvetanova United States	11	654 1.2×	248 1.0×	54 0.8×	17 0.3×	38 0.7×	17	754
Thomas McAvoy United States	14	601 1.1×	176 0.7×	35 0.5×	19 0.3×	58 1.0×	19	822
Albert J. Uveges United States	9	401 0.7×	198 0.8×	23 0.3×	20 0.3×	72 1.3×	11	658
J. Robert Bostwick United States	11	309 0.6×	155 0.7×	27 0.4×	34 0.5×	31 0.5×	23	532
Amanda K. Nosie United States	3	262 0.5×	80 0.3×	42 0.6×	52 0.8×	50 0.9×	5	603
Laura A. Price United States	10	419 0.8×	211 0.9×	65 1.0×	24 0.4×	14 0.2×	13	629
Phan Trieu Canada	15	925 1.7×	483 2.0×	68 1.0×	14 0.2×	32 0.6×	20	1.1k

Countries citing papers authored by Yuki Ono

Since Specialization

Citations

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

Fields of papers citing papers by Yuki Ono

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuki Ono

This figure shows the co-authorship network connecting the top 25 collaborators of Yuki Ono. A scholar is included among the top collaborators of Yuki Ono 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 Yuki Ono. Yuki Ono is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

15 of 15 papers shown

Maeda, Takashi, Eiji Tsujita, Naotaka Hashimoto, et al.. (2024). Skeletal Muscle Mass Index Reduction Rate as a Prognostic Indicator for Patients Undergoing Pancreatectomy for Pancreatic Cancer. Cancer Diagnosis & Prognosis. 4(3). 301–308. 1 indexed citations

Ono, Yuki, Yuka Kobayashi, Jiro Ogura, et al.. (2024). Cost-Effectiveness Analysis of FOLFIRI-Based First-Line Regimens for Metastatic Colorectal Cancer Using Clinical Decision Analysis.. PubMed. 51(5). 541–547. 1 indexed citations

Shirasawa, Hiromitsu, et al.. (2023). An approach for live imaging of first cleavage in mouse embryos using fluorescent chemical probes for DNA, microtubules, and microfilaments. Reproductive Medicine and Biology. 22(1). e12551–e12551. 2 indexed citations

Maeda, Takashi, Eiji Tsujita, Kyohei Yugawa, et al.. (2023). A case of difficult-to-diagnose hepatic reactive lymphoid hyperplasia finally diagnosed by using PCR analysis of IgH-gene rearrangements: a case report. International Cancer Conference Journal. 13(1). 33–39.

Kishi, Takayuki, Satoru Ishida, Hiroki Kawana, et al.. (2023). Ectodomain shedding of EGFR ligands serves as an activation readout for TRP channels. PLoS ONE. 18(1). e0280448–e0280448. 4 indexed citations

Ono, Yuki, et al.. (2023). Generation of Gαi knock-out HEK293 cells illuminates Gαi-coupling diversity of GPCRs. Communications Biology. 6(1). 112–112. 8 indexed citations

Hauge, M., Daniel J. Scott, Meritxell Canals, et al.. (2022). OZITX, a pertussis toxin-like protein for occluding inhibitory G protein signalling including Gαz. Communications Biology. 5(1). 256–256. 11 indexed citations

Kawakami, Kouki, Masataka Yanagawa, Yuki Ono, et al.. (2022). Heterotrimeric Gq proteins act as a switch for GRK5/6 selectivity underlying β-arrestin transducer bias. Nature Communications. 13(1). 487–487. 59 indexed citations

Kise, Ryoji, Yuki Ono, Kouki Kawakami, & Asuka Inoue. (2020). Toward understanding the role of G-protein signaling. Current Opinion in Endocrine and Metabolic Research. 16. 51–55. 1 indexed citations

10.

Kozielewicz, Paweł, Ainoleena Turku, Julian Petersen, et al.. (2020). Structural insight into small molecule action on Frizzleds. Nature Communications. 11(1). 414–414. 48 indexed citations

11.

Inoue, Asuka, Francesco Raimondi, Francois Marie Ngako Kadji, et al.. (2019). Illuminating G-Protein-Coupling Selectivity of GPCRs. Cell. 177(7). 1933–1947.e25. 396 indexed citations breakdown →

12.

Hisano, Yu, Mari Kono, Andréane Cartier, et al.. (2019). Lysolipid receptor cross-talk regulates lymphatic endothelial junctions in lymph nodes. The Journal of Experimental Medicine. 216(7). 1582–1598. 49 indexed citations

13.

Kuo, Bryan, Erzsébet Szabó, Sue Çhin Lee, et al.. (2018). The LPA2 receptor agonist Radioprotectin-1 spares Lgr5-positive intestinal stem cells from radiation injury in murine enteroids. Cellular Signalling. 51. 23–33. 19 indexed citations

14.

Ono, Yuki, Shinya Wada, Masanori Izumi, Amane Makino, & H. Ishida. (2012). Evidence for contribution of autophagy to Rubisco degradation during leaf senescence in Arabidopsis thaliana. Plant Cell & Environment. 36(6). 1147–1159. 76 indexed citations

15.

Hojo, H, et al.. (1996). Differential production of interleukin-6 and its close relation to liver metastasis in clones from murine P815 mastocytoma. Cancer Letters. 108(1). 55–59. 7 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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