Kiyoshi Nagai

13.7k citations
215 papers · 10.6k indexed · 2 hit papers · h-index 51

Kiyoshi Nagai

207 papers receiving 10.2k citations

Hit Papers

RNA Splicing by...4261990202620022014100200300400500

Peers

Kiyoshi Nagai
Comparison fields: 5 of 169
  • Cell Biology 2.1k
  • Structural Biology 156
  • Molecular Biology 7.4k
  • Genetics 494
  • Control and Systems Engineering 799
Replace Carl Wu with:
Carl Wu United States
David E. Hill United States
Minoru Takata Japan
Andre Levchenko United States
Guillaume Charras United Kingdom
Mike Strauss Germany
Dan Shi United States
Gaudenz Danuser United States
Richard Nuccitelli United States
Ken Jacobson United States
Kiyoshi Nagai relative to Carl Wu United States Carl Wu's profile →
Citations per field
00.5×10×15×20×24.2×
Carl Wu · 1×
Citations per year

Countries citing papers authored by Kiyoshi Nagai

Since Specialization
Citations

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

Fields of papers citing papers by Kiyoshi Nagai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Kiyoshi Nagai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kiyoshi Nagai Line = papers co-authored together Kiyoshi Nagai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20230
3 202137
4 201988
5 2016180
6 2016168
7 20157
8 20151
9 2010162
10 200741
11
Deposition mechanism of trace metals on silicon wafer surfaces in ultra pure water
20000
12 199414
13 19949
14 19932
15 199117
16 199018
17
Crystal structure of the RNA-binding domain of the U1 small nuclear ribonucleoprotein Abreakdown →
1990572
18 19875
19 19869
20 19863

About Kiyoshi Nagai

Kiyoshi Nagai is a scholar working on Cell Biology, Control and Systems Engineering and Molecular Biology, having authored 215 papers that have together received 10.6k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (68 papers), RNA Research and Splicing (61 papers), RNA modifications and cancer (48 papers), Hemoglobin structure and function (43 papers), Robotic Mechanisms and Dynamics (33 papers), Robot Manipulation and Learning (30 papers), Soft Robotics and Applications (23 papers) and Neonatal Health and Biochemistry (18 papers). The work is most often cited by research in Cell Biology (2.1k citations), Structural Biology (156 citations) and Molecular Biology (7.4k citations). Kiyoshi Nagai has collaborated with scholars based in United Kingdom, Japan and United States. Frequent co-authors include Chris Oubridge, Hans Christian Thøgersen, Max E. Wilkinson, Andrew J. Newman, Jade Li, Teizo Kitagawa, Philip R. Evans, Clément Charenton, Wojciech P. Galej and Gabriele Varani. Their work appears in journals such as Nature, Science and Chemical Reviews.

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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