Ken Saida

997 citations
38 papers · 276 · h-index 10

Impact in

  • Nephrology top 10%
    • Renal Diseases and Glomerulopathies
    • Genetic and Kidney Cyst Diseases
    • Genetic Syndromes and Imprinting
    • Blood disorders and treatments

Papers in

    • Renal and related cancers 4
    • Hedgehog Signaling Pathway Studies 3
    • RNA modifications and cancer 3
    • Genetic Syndromes and Imprinting 5
    • Genetic and Kidney Cyst Diseases 4
    • Genetics and Neurodevelopmental Disorders 3

Ken Saida

36 papers receiving 273 citations

Peers

Ken Saida
Comparison fields: 5 of 54
  • Nephrology 51
  • Genetics 85
  • Genetics 27
  • Immunology 39
  • Hematology 19
Replace Linus A. Völker with:
Linus A. Völker Germany
Jessica K. Edwards United Kingdom
Kalpana Gowrishankar India
Margherita Baldassarri Italy
Seongmin Choi South Korea
Ming Juan Ye Japan
Diana M. Iglesias Canada
Philip L. Beales United Kingdom
Katsuyoshi Kanemoto Japan
Andrea Alonso United States
Ken Saida relative to Linus A. Völker Germany Linus A. Völker's profile →
Citations per field
00.5×1.5×2.3×
Linus A. Völker · 1×
Citations per year

Countries citing papers authored by Ken Saida

Since Specialization
Citations

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

Fields of papers citing papers by Ken Saida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201439
2 202025
3 201520
4 202118
5 201518
6 201712
7 200411
8 201810
9 201410
10 202010
11 20139
12 20209
13 20199
14 20197
15 20216
16 20216
17 19916
18 20135
19 20174
20 20204

About Ken Saida

Ken Saida is a scholar working on Molecular Biology, Genetics, Nephrology, Pulmonary and Respiratory Medicine and Hematology, having authored 38 papers that have together received 276 indexed citations. Recurring topics across this work include Renal Diseases and Glomerulopathies (6 papers), Genetic Syndromes and Imprinting (5 papers), Renal and related cancers (4 papers), Genetic and Kidney Cyst Diseases (4 papers), Complement system in diseases (3 papers), Genetics and Neurodevelopmental Disorders (3 papers), Hedgehog Signaling Pathway Studies (3 papers) and RNA modifications and cancer (3 papers). The work is most often cited by research in Nephrology (51 citations), Genetics (85 citations), Genetics (27 citations), Immunology (39 citations) and Hematology (19 citations). Ken Saida has collaborated with scholars based in Japan, United States and Brazil. Frequent co-authors include Masao Ogura, Koichi Kamei, Mai Sato, Naomichi Matsumoto, Takeshi Mizuguchi, H. Machida, Shuichi Ito, Shuichi Ito, Masaki Takahashi and Atsushi Fujita. Their work appears in journals such as Brain and Development, Nephrology, Frontiers in Pediatrics, European Journal of Pediatrics and Human Genetics.

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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