K Segawa

1.4k citations
28 papers · 1.2k indexed · 1 hit paper · h-index 14

K Segawa

27 papers receiving 1.2k citations

Hit Papers

The consensus motif for phosphorylation by cyclin D1-Cdk4...5181996202620062016100200300400500

Peers

K Segawa
Comparison fields: 5 of 76
  • Oncology 640
  • Cell Biology 193
  • Molecular Biology 810
  • Immunology 180
  • Biotechnology 63
Replace G H Enders with:
G H Enders United States
N B La Thangue United Kingdom
Leah Lipsich United States
Wendy W. Colby United States
J R Nevins United States
Rozanne Arulanandam Canada
Maureen O. Weeks United States
Chun Jeih Ryu South Korea
Eberhard Krausz Germany
Robert F. Harvey United Kingdom
K Segawa relative to G H Enders United States G H Enders's profile →
Citations per field
00.5×3.7×
G H Enders · 1×
Citations per year

Countries citing papers authored by K Segawa

Since Specialization
Citations

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

Fields of papers citing papers by K Segawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20242
3 20242
4 20242
5 201416
6 201245
7
Increased expression of highly branched N-glycans at cell surface is correlated with the malignant phenotypes of mouse tumor cells.
199787
8
The 273rd codon mutants of p53 show growth modulation activities not correlated with p53-specific transactivation activity.
199625
9 199526
10
Phosphorylation of E2F-1 by cyclin A-cdk2.
199587
11 199426
12 198711
13 198710
14 19837
15 198321
16
Oncogene and its production of an avian sarcoma virus Y73.
19821
17 19829
18 198250
19 1980162
20
Antisera from mice and rats incubated with syngeneic Rous sarcoma cells.
19803

About K Segawa

K Segawa is a scholar working on Oncology, Genetics and Ecology, having authored 28 papers that have together received 1.2k indexed citations. Recurring topics across this work include Virus-based gene therapy research (9 papers), Polyomavirus and related diseases (8 papers), Bacteriophages and microbial interactions (6 papers), Cancer-related Molecular Pathways (5 papers), Organic Light-Emitting Diodes Research (4 papers), Glycosylation and Glycoproteins Research (2 papers), RNA Interference and Gene Delivery (2 papers) and RNA modifications and cancer (2 papers). The work is most often cited by research in Oncology (640 citations), Cell Biology (193 citations) and Molecular Biology (810 citations). K Segawa has collaborated with scholars based in Japan, United States and Australia. Frequent co-authors include Yoichi Taya, Ikuko Suzuki‐Takahashi, Hideaki Higashi, Susumu Nishimura, Masatoshi Kitagawa, Katsuyuki Tamai, Hai Kwan Jung, Eisaku Yoshida, M. Ikeda and Jun‐ya Kato. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and The EMBO Journal.

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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2026