T. OKUDA

88 papers receiving 1.5k citations

Peers

T. OKUDA
Comparison fields: 5 of 112
  • Molecular Medicine 119
  • Applied Microbiology and Biotechnology 45
  • Endocrinology 84
  • Immunology 281
  • Pharmacology 219
Replace Tushar Kanti Maiti with:
Tushar Kanti Maiti India
Eun Young Park South Korea
Fabrizio Gentile Italy
Junya Nagai Japan
Hitoshi Kojo Japan
Martina Perše Slovenia
Marina Pinheiro Portugal
Yamei Yu China
Chiung‐Tong Chen Taiwan
Michael A. Cook Canada
T. OKUDA relative to Tushar Kanti Maiti India Tushar Kanti Maiti's profile →
Citations per field
00.5×4.7×
Tushar Kanti Maiti · 1×
Citations per year

Countries citing papers authored by T. OKUDA

Since Specialization
Citations

This map shows the geographic impact of T. OKUDA'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 T. OKUDA with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. OKUDA more than expected).

Fields of papers citing papers by T. OKUDA

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006148
2 2005133
3 1992111
4
Passive transfer of autoimmune induced hypertension in the rat by lymph node cells.
196794
5 200984
6 199750
7 200645
8
Development of an assay for aryl hydrocarbon (benzo(a)pyrene) hydroxylase in human peripheral blood monocytes.
197645
9 200444
10 198242
11 199136
12 200033
13 200029
14 201029
15 201226
16 200326
17 199225
18 199025
19 199022
20 200921

About T. OKUDA

T. OKUDA is a scholar working on Molecular Biology, Immunology, Organic Chemistry, Pharmacology and Radiology, Nuclear Medicine and Imaging, having authored 92 papers that have together received 1.6k indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (25 papers), Monoclonal and Polyclonal Antibodies Research (12 papers), Carbohydrate Chemistry and Synthesis (9 papers), Antibiotics Pharmacokinetics and Efficacy (6 papers), Antibiotic Resistance in Bacteria (6 papers), Galectins and Cancer Biology (5 papers), Immune Cell Function and Interaction (5 papers) and Phytochemicals and Antioxidant Activities (5 papers). The work is most often cited by research in Molecular Medicine (119 citations), Applied Microbiology and Biotechnology (45 citations), Endocrinology (84 citations), Immunology (281 citations) and Pharmacology (219 citations). T. OKUDA has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Arthur P. Grollman, Koichi Furukawa, MASATOMO FUKASAWA, Keiko Furukawa, Yoshihiro Sumita, Takeshi Urano, Hiroki Matsui, Noriyo Tokuda, Ken-ichi Nakayama and Tomoharu Tanio. Their work appears in journals such as Antimicrobial Agents and Chemotherapy, Scientific Reports, Biochemical and Biophysical Research Communications, Data in Brief and Tetrahedron.

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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