Ai Okada

433 total citations
9 papers, 79 citations indexed

About

Ai Okada is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Oncology. According to data from OpenAlex, Ai Okada has authored 9 papers receiving a total of 79 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Pathology and Forensic Medicine and 2 papers in Oncology. Recurrent topics in Ai Okada's work include RNA modifications and cancer (3 papers), RNA and protein synthesis mechanisms (3 papers) and RNA Research and Splicing (3 papers). Ai Okada is often cited by papers focused on RNA modifications and cancer (3 papers), RNA and protein synthesis mechanisms (3 papers) and RNA Research and Splicing (3 papers). Ai Okada collaborates with scholars based in Japan, United States and Taiwan. Ai Okada's co-authors include Yuichi Shiraishi, Kenichi Chiba, Keisuke Kataoka, Hiroko Tanaka, Satoru Miyano, Yasunori Kogure, Seishi Ogawa, Yuki Saito, Junji Koya and Yasuhito Arai and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Blood.

In The Last Decade

Ai Okada

7 papers receiving 78 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ai Okada Japan	4	60	18	15	8	5	9	79
Catalina Anghel Canada	3	44 0.7×	35 1.9×	16 1.1×	12 1.5×	3 0.6×	10	79
Orla Deevy Ireland	2	116 1.9×	17 0.9×	21 1.4×	3 0.4×	3 0.6×	3	129
Shohei Noma Japan	4	124 2.1×	36 2.0×	10 0.7×	9 1.1×	3 0.6×	9	140
Caterina Lucano Italy	4	68 1.1×	9 0.5×	18 1.2×	23 2.9×	3 0.6×	5	92
Marlena Mucha Germany	3	158 2.6×	20 1.1×	23 1.5×	8 1.0×	3 0.6×	5	168
Alexandr Boytsov Russia	3	88 1.5×	14 0.8×	28 1.9×	4 0.5×	2 0.4×	5	113
Tony Yammine Lebanon	5	86 1.4×	12 0.7×	37 2.5×	4 0.5×	8 1.6×	14	126
Krupa S. Jani United States	5	118 2.0×	9 0.5×	15 1.0×	4 0.5×	2 0.4×	8	140
Mattias Van Heetvelde Belgium	5	59 1.0×	17 0.9×	28 1.9×	9 1.1×	1 0.2×	10	89
Marie Bernkopf Austria	5	40 0.7×	15 0.8×	23 1.5×	8 1.0×		8	74

Countries citing papers authored by Ai Okada

Since Specialization

Citations

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

Fields of papers citing papers by Ai Okada

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ai Okada

This figure shows the co-authorship network connecting the top 25 collaborators of Ai Okada. A scholar is included among the top collaborators of Ai Okada 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 Ai Okada. Ai Okada 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:

9 of 9 papers shown

1.

Iida, Naoko, Ai Okada, Yoshihisa Kobayashi, et al.. (2025). Systematically developing a registry of splice-site creating variants utilizing massive publicly available transcriptome sequence data. Nature Communications. 16(1). 426–426. 1 indexed citations

2.

Yoshifuji, Kota, Yuki Saito, Mariko Tabata, et al.. (2025). In vivo CRISPR screening reveals cooperation of KMT2D and TP53 deficiencies in B-cell lymphomagenesis. Blood Advances. 9(19). 5040–5055.

3.

Fujimoto, Ayumi, Seiji Sakata, Keisuke Kataoka, et al.. (2025). High-accuracy Detection of PD-L1 3’-UTR Disruption by Immunohistochemistry and Fluorescence in Situ Hybridization on Formalin-fixed Paraffin-embedded Sections. The American Journal of Surgical Pathology. 49(5). 490–498.

4.

Shiraishi, Yuichi, Junji Koya, Kenichi Chiba, et al.. (2023). Precise characterization of somatic complex structural variations from tumor/control paired long-read sequencing data with nanomonsv. Nucleic Acids Research. 51(14). e74–e74. 18 indexed citations

5.

Shiraishi, Yuichi, Ai Okada, Kenichi Chiba, et al.. (2022). Systematic identification of intron retention associated variants from massive publicly available transcriptome sequencing data. Nature Communications. 13(1). 5357–5357. 12 indexed citations

6.

Shiraishi, Yuichi, Keisuke Kataoka, Kenichi Chiba, et al.. (2018). A comprehensive characterization of cis -acting splicing-associated variants in human cancer. Genome Research. 28(8). 1111–1125. 41 indexed citations

7.

Ochi, Yotaro, Kenichi Yoshida, Ying‐Jung Huang, et al.. (2018). Molecular Profiling of Blastic Transformation in Chronic Myeloid Leukemia. Blood. 132(Supplement 1). 1725–1725. 3 indexed citations

8.

Okada, Ai, Kenichi Chiba, Hiroko Tanaka, Satoru Miyano, & Yuichi Shiraishi. (2017). A framework for generating interactive reports for cancer genome analysis. The Journal of Open Source Software. 2(20). 457–457. 1 indexed citations

9.

Aizawa, Katsuji, et al.. (2007). METABOLIC EFFECTS OF RAPID WEIGHT LOSS IN ELITE ATHLETES. Japanese Journal of Physical Fitness and Sports Medicine. 56(4). 429–436. 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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