Seiichi Ishida

5.1k citations
70 papers · 3.9k · 1 hit paper · h-index 24

Impact in

Papers in

    • Gene expression and cancer classification 6
    • Epigenetics and DNA Methylation 5
    • Drug Transport and Resistance Mechanisms 9
    • Cancer-related Molecular Pathways 7

Seiichi Ishida

68 papers receiving 3.8k citations

Seiichi Ishida's Hit Papers

Predicting the clinical status of human breast cancer by using gene expression profiles 2001 · 993 citations
9930+8+16Years since publication250500750

Peers

Seiichi Ishida
Comparison fields: 5 of 133
  • Oncology 1.2k
  • Cancer Research 497
  • Molecular Biology 2.3k
  • Pharmacology 258
  • Hepatology 162
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Seiichi Ishida relative to Andrew N. Billin United States Andrew N. Billin's profile →
Citations per field
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Citations per year

Countries citing papers authored by Seiichi Ishida

Since Specialization
Citations

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

Fields of papers citing papers by Seiichi Ishida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Predicting the clinical status of human breast cancer by using gene expression profiles
Hit paper breakdown →
2001993
2 2001488
3 1998309
4 2000232
5 2003189
6 2000149
7 2000133
8 200896
9 200194
10 200390
11 200270
12 201470
13 201866
14 200462
15
Distinct gene expression phenotypes of cells lacking Rb and Rb family members.
200360
16 200252
17 200551
18 200951
19 200543
20 200541

About Seiichi Ishida

Seiichi Ishida is a scholar working on Molecular Biology, Oncology, Biomedical Engineering, Pharmacology and Hepatology, having authored 70 papers that have together received 3.9k indexed citations. Recurring topics across this work include 3D Printing in Biomedical Research (14 papers), Pharmacogenetics and Drug Metabolism (11 papers), Liver physiology and pathology (10 papers), Drug Transport and Resistance Mechanisms (9 papers), Cancer-related Molecular Pathways (7 papers), Gene expression and cancer classification (6 papers), Epigenetics and DNA Methylation (5 papers) and Computational Drug Discovery Methods (5 papers). The work is most often cited by research in Oncology (1.2k citations), Cancer Research (497 citations), Molecular Biology (2.3k citations), Pharmacology (258 citations) and Hepatology (162 citations). Seiichi Ishida has collaborated with scholars based in Japan, United States and Sri Lanka. Frequent co-authors include Joseph R. Nevins, Erich Huang, Mike West, Harry Zuzan, Rainer Spang, Holly K. Dressman, Laszlo Jakoi, Jeffrey R. Marks, Carrie Blanchette and John A. Olson. Their work appears in journals such as Drug Metabolism and Disposition, Biochemical and Biophysical Research Communications, Biological and Pharmaceutical Bulletin, Drug Metabolism and Pharmacokinetics and Molecular and Cellular Biology.

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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