Daisuke Kaida

2.6k total citations · 2 hit papers
27 papers, 1.9k citations indexed

About

Daisuke Kaida is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Daisuke Kaida has authored 27 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 3 papers in Oncology and 2 papers in Cell Biology. Recurrent topics in Daisuke Kaida's work include RNA Research and Splicing (24 papers), RNA modifications and cancer (18 papers) and RNA and protein synthesis mechanisms (12 papers). Daisuke Kaida is often cited by papers focused on RNA Research and Splicing (24 papers), RNA modifications and cancer (18 papers) and RNA and protein synthesis mechanisms (12 papers). Daisuke Kaida collaborates with scholars based in Japan, United States and Italy. Daisuke Kaida's co-authors include Ihab Younis, Gideon Dreyfuss, Michael G. Berg, Lili Wan, Larry N. Singh, Minoru Yoshida, Mumtaz Kasim, Tokio Tani, Hidenori Nakajima and Ken Ishigami and has published in prestigious journals such as Nature, Cell and Nucleic Acids Research.

In The Last Decade

Daisuke Kaida

26 papers receiving 1.9k citations

Hit Papers

Spliceostatin A targets SF3b and inhibits both splicing a... 2007 2026 2013 2019 2007 2010 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daisuke Kaida Japan 16 1.8k 208 122 73 70 27 1.9k
Haihong Shen South Korea 22 1.9k 1.0× 274 1.3× 130 1.1× 74 1.0× 66 0.9× 66 2.1k
Jacky Chi Ki Ngo Hong Kong 19 893 0.5× 87 0.4× 83 0.7× 33 0.5× 90 1.3× 45 1.2k
Marie-Ève Beaulieu Spain 15 782 0.4× 156 0.8× 72 0.6× 32 0.4× 44 0.6× 29 1.1k
Berit Olsen Krogh United States 17 1.2k 0.7× 158 0.8× 51 0.4× 146 2.0× 81 1.2× 23 1.4k
Nathaniel Robichaud Canada 12 1.6k 0.9× 252 1.2× 91 0.7× 27 0.4× 88 1.3× 14 1.9k
Marie‐Eve Lalonde Canada 11 1.4k 0.8× 142 0.7× 43 0.4× 83 1.1× 24 0.3× 13 1.5k
Rob C. Laister Canada 17 875 0.5× 75 0.4× 65 0.5× 51 0.7× 139 2.0× 33 1.2k
Olivier Binda Canada 19 958 0.5× 148 0.7× 29 0.2× 49 0.7× 64 0.9× 30 1.1k

Countries citing papers authored by Daisuke Kaida

Since Specialization
Citations

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

Fields of papers citing papers by Daisuke Kaida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daisuke Kaida

This figure shows the co-authorship network connecting the top 25 collaborators of Daisuke Kaida. A scholar is included among the top collaborators of Daisuke Kaida 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 Daisuke Kaida. Daisuke Kaida 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.
Kaida, Daisuke, Takashi Miyata, Tomoharu Miyashita, et al.. (2022). Intra-tumoral FGFR2 Expression Predicts Prognosis and Chemotherapy Response in Advanced HER2-positive Gastric Cancer Patients. Cancer Diagnosis & Prognosis. 2(3). 293–299. 2 indexed citations
2.
Kaida, Daisuke, et al.. (2022). Spliceostatin A stabilizes CDKN1B mRNA through the 3′ UTR. Biochemical and Biophysical Research Communications. 608. 39–44. 3 indexed citations
3.
Yoshimoto, Rei, Tilman Schneider‐Poetsch, Masaaki Furuno, et al.. (2021). Spliceostatin A interaction with SF3B limits U1 snRNP availability and causes premature cleavage and polyadenylation. Cell chemical biology. 28(9). 1356–1365.e4. 11 indexed citations
4.
Kataoka, Naoyuki, et al.. (2020). Rbm38 Reduces the Transcription Elongation Defect of the SMEK2 Gene Caused by Splicing Deficiency. International Journal of Molecular Sciences. 21(22). 8799–8799. 2 indexed citations
5.
Kaida, Daisuke. (2019). Spliceostatin A treatment inhibits mitotic clonal expansion and adipogenesis. Biochemical and Biophysical Research Communications. 514(3). 848–852. 3 indexed citations
6.
Yoshimoto, Rei, Daisuke Kaida, Masaaki Furuno, et al.. (2016). Global analysis of pre-mRNA subcellular localization following splicing inhibition by spliceostatin A. RNA. 23(1). 47–57. 51 indexed citations
7.
Satoh, Takayuki & Daisuke Kaida. (2016). Upregulation of p27 cyclin-dependent kinase inhibitor and a C-terminus truncated form of p27 contributes to G1 phase arrest. Scientific Reports. 6(1). 27829–27829. 34 indexed citations
8.
Kakeya, Hideaki, et al.. (2015). RQN-18690A (18-deoxyherboxidiene) targets SF3b, a spliceosome component, and inhibits angiogenesis. The Journal of Antibiotics. 69(2). 121–123. 7 indexed citations
9.
Çolak, Recep, Joan Teyra, Carles Corbi‐Verge, et al.. (2015). Semi-supervised Learning Predicts Approximately One Third of the Alternative Splicing Isoforms as Functional Proteins. Cell Reports. 12(2). 183–189. 18 indexed citations
10.
Kaida, Daisuke, et al.. (2015). Splicing inhibition decreases phosphorylation level of Ser2 in Pol II CTD. Nucleic Acids Research. 43(17). 8258–8267. 37 indexed citations
11.
Satoh, Takayuki, et al.. (2014). U2 snRNP Is Required for Expression of the 3′ End of Genes. PLoS ONE. 9(5). e98015–e98015. 20 indexed citations
12.
Kaida, Daisuke, Tilman Schneider‐Poetsch, & Minoru Yoshida. (2012). Splicing in oncogenesis and tumor suppression. Cancer Science. 103(9). 1611–1616. 51 indexed citations
13.
Berg, Michael G., Larry N. Singh, Ihab Younis, et al.. (2012). U1 snRNP Determines mRNA Length and Regulates Isoform Expression. Cell. 150(1). 53–64. 357 indexed citations
14.
Kaida, Daisuke, Michael G. Berg, Ihab Younis, et al.. (2010). U1 snRNP protects pre-mRNAs from premature cleavage and polyadenylation. Nature. 468(7324). 664–668. 501 indexed citations breakdown →
15.
Schneider‐Poetsch, Tilman, Takeo Usui, Daisuke Kaida, & Minoru Yoshida. (2010). Garbled messages and corrupted translations. Nature Chemical Biology. 6(3). 189–198. 19 indexed citations
16.
Kaida, Daisuke, Hajime Motoyoshi, Etsu Tashiro, et al.. (2007). Spliceostatin A targets SF3b and inhibits both splicing and nuclear retention of pre-mRNA. Nature Chemical Biology. 3(9). 576–583. 520 indexed citations breakdown →
17.
Kaida, Daisuke, Shinichi Nishimura, Akihisa Matsuyama, et al.. (2007). Inhibition of splicing and nuclear retention of pre-mRNA by spliceostatin A in fission yeast. Biochemical and Biophysical Research Communications. 364(3). 573–577. 25 indexed citations
18.
Kaida, Daisuke, Akio Toh‐e, & Yoshiko Kikuchi. (2003). Rsp5–Bul1/2 complex is necessary for the HSE-mediated gene expression in budding yeast. Biochemical and Biophysical Research Communications. 306(4). 1037–1041. 19 indexed citations
19.
Kaida, Daisuke, Hideki Yashiroda, Akio Toh‐e, & Yoshiko Kikuchi. (2002). Yeast Whi2 and Psr1‐phosphatase form a complex and regulate STRE‐mediated gene expression. Genes to Cells. 7(6). 543–552. 76 indexed citations
20.
Yashiroda, Hideki, Daisuke Kaida, Akio Toh‐e, & Yoshiko Kikuchi. (1998). The PY-motif of Bul1 protein is essential for growth of Saccharomyces cerevisiae under various stress conditions. Gene. 225(1-2). 39–46. 49 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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