Rina Okada

623 citations
26 papers · 475 · h-index 12

Impact in

  • Hepatology top 10%
    • Hepatitis C virus research
  • Nephrology top 10%
    • Chronic Kidney Disease and Diabetes

Papers in

Rina Okada

26 papers receiving 468 citations

Peers

Rina Okada
Comparison fields: 5 of 71
  • Hepatology 44
  • Nephrology 39
  • Computational Mathematics 3
  • Cancer Research 64
  • Genetics 30
Replace Hongsi Jiang with:
Hongsi Jiang United States
Shiroh Tanoue Japan
Saiful A. Mir United States
Yifang Hu China
Tümen Mansuroglu Germany
Weiqi Tan China
Mahmoud Al‐Azab China
Ghaffar Muharram France
Rina Okada relative to Hongsi Jiang United States Hongsi Jiang's profile →
Citations per field
00.5×4.8×
Hongsi Jiang · 1×
Citations per year

Countries citing papers authored by Rina Okada

Since Specialization
Citations

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

Fields of papers citing papers by Rina Okada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201382
2 201574
3 201457
4 201439
5 200132
6 201525
7 202020
8 201517
9 201716
10 201814
11 201314
12 201412
13 202311
14 201310
15 200710
16 20128
17 20207
18 20166
19 20186
20 20215

About Rina Okada

Rina Okada is a scholar working on Molecular Biology, Epidemiology, Surgery, Genetics and Hepatology, having authored 26 papers that have together received 475 indexed citations. Recurring topics across this work include Hepatitis B Virus Studies (5 papers), Helicobacter pylori-related gastroenterology studies (4 papers), Hepatitis C virus research (3 papers), Natural product bioactivities and synthesis (3 papers), Advances in Cucurbitaceae Research (3 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Pluripotent Stem Cells Research (2 papers) and Genetic Neurodegenerative Diseases (2 papers). The work is most often cited by research in Hepatology (44 citations), Nephrology (39 citations), Computational Mathematics (3 citations), Cancer Research (64 citations) and Genetics (30 citations). Rina Okada has collaborated with scholars based in Japan, Indonesia and South Korea. Frequent co-authors include Toshihito Tanahashi, Takeshi Azuma, Yoshiki Murakami, Yohei Okada, Yasushi Kanazawa, Jun Kinoshita, Tamotsu Yokota, Daiji Kawanami, Manabu Doyu and Kazunori Utsunomiya. Their work appears in journals such as Gut Pathogens, Biochemical and Biophysical Research Communications, Molecular Brain, Gastroenterology and Journal of Clinical Microbiology.

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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