KEN IKEDA

1.4k citations
87 papers · 1.2k · h-index 18

Impact in

Papers in

KEN IKEDA

83 papers receiving 1.1k citations

Peers

KEN IKEDA
Comparison fields: 5 of 102
  • Pharmaceutical Science 335
  • Spectroscopy 280
  • Molecular Medicine 81
  • Analytical Chemistry 109
  • Pharmacology 63
Replace V.J. Stella with:
V.J. Stella United States
Edwin T. Sugita United States
Neelam Seedher India
Staffan Tavelin Sweden
Gábor Vasvári Hungary
W. Morozowich United States
Takashi Mano Japan
Manabu Nakatani Japan
Oksana Tsinman United States
Avital Beig Israel
KEN IKEDA relative to V.J. Stella United States V.J. Stella's profile →
Citations per field
00.5×1.5×2.0×
V.J. Stella · 1×
Citations per year

Countries citing papers authored by KEN IKEDA

Since Specialization
Citations

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

Fields of papers citing papers by KEN IKEDA

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside KEN IKEDA, 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 KEN IKEDA Line = papers co-authored together KEN IKEDA links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1987132
2 198968
3 197749
4 197647
5 197644
6 199243
7 197543
8 198042
9 199139
10 197937
11 197535
12 197832
13 199531
14 198329
15 197926
16 197421
17 197919
18 200218
19 198216
20 199216

About KEN IKEDA

KEN IKEDA is a scholar working on Molecular Biology, Organic Chemistry, Spectroscopy, Materials Chemistry and Signal Processing, having authored 87 papers that have together received 1.2k indexed citations. Recurring topics across this work include Protein Interaction Studies and Fluorescence Analysis (27 papers), Analytical Chemistry and Chromatography (24 papers), Chemical Reaction Mechanisms (14 papers), Lanthanide and Transition Metal Complexes (11 papers), Drug Solubulity and Delivery Systems (10 papers), Advanced Data Compression Techniques (10 papers), Surfactants and Colloidal Systems (8 papers) and Digital Filter Design and Implementation (8 papers). The work is most often cited by research in Pharmaceutical Science (335 citations), Spectroscopy (280 citations), Molecular Medicine (81 citations), Analytical Chemistry (109 citations) and Pharmacology (63 citations). KEN IKEDA has collaborated with scholars based in Japan, United States and Denmark. Frequent co-authors include Toshihisa Yotsuyanagi, Yukihisa Kurono, Kaneto Uekama, Masaki Otagiri, Fumitoshi Hirayama, Mariko Nagata, Shigekazu Ito, Danni Chen, Takehiro Moriya and Ikuo Kushida. Their work appears in journals such as Chemical and Pharmaceutical Bulletin, Journal of Pharmaceutical Sciences, Journal of Pharmacy and Pharmacology, International Journal of Pharmaceutics and IEEE Transactions on Consumer Electronics.

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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