Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Antibodies to adult t‐cell leukemia‐virus‐associated antigen (atla) in sera from patients with atl and controls in japan: A nation‐wide sero‐epidemiologic study
1982490 citationsYorio Hinuma, Haruko Komoda et al.International Journal of Cancerprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of K. Yunoki'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. Yunoki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K. Yunoki more than expected).
This network shows the impact of papers produced by K. Yunoki. 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. Yunoki. The network helps show where K. Yunoki may publish in the future.
Co-authorship network of co-authors of K. Yunoki
This figure shows the co-authorship network connecting the top 25 collaborators of K. Yunoki.
A scholar is included among the top collaborators of K. Yunoki based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with K. Yunoki. K. Yunoki is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Matsumoto, Takao, et al.. (1986). [Immunologic characterization of lymphoid tumor cells from adult T-cell leukemia (ATL) and peripheral T-cell lymphoma (PTCL) in an ATL-endemic area].. PubMed. 27(5). 693–700.1 indexed citations
6.
Nomura, Kazushi, et al.. (1985). [The outbreak of five lymphoid malignancies in one family during seven years].. PubMed. 26(6). 974–9.2 indexed citations
7.
Utsunomiya, Atae, T Matsumoto, Masahiro Matsumoto, et al.. (1985). Severe diarrhea and intestinal strongyloidiasis in a patient with adult T-cell leukemia.. PubMed. 48(4). 1109–13.5 indexed citations
8.
Utsunomiya, Atae, Mitsunobu Matsumoto, Takao Matsumoto, et al.. (1983). A report of a case of T-cell-derived chronic lymphocytic leukemia with antibodies to adult T-cell leukemia-associated antigens.. PubMed. 13 Suppl 2. 291–9.6 indexed citations
9.
Utsunomiya, Atae, et al.. (1983). Refractory diarrhea in a patient with adult T cell leukemia.. PubMed. 46(4). 1010–5.3 indexed citations
10.
Matsumoto, Takao, K. Yunoki, Shuichi Hanada, et al.. (1983). Hodgkin's disease in the endemic area of adult T-cell leukemia (ATL).. PubMed. 13 Suppl 2. 301–8.1 indexed citations
11.
Hinuma, Yorio, Haruko Komoda, Toru Chosa, et al.. (1982). Antibodies to adult t‐cell leukemia‐virus‐associated antigen (atla) in sera from patients with atl and controls in japan: A nation‐wide sero‐epidemiologic study. International Journal of Cancer. 29(6). 631–635.490 indexed citations breakdown →
Yunoki, K. & A. Clark Griffin. (1961). Composition and properties of a highly purified toxohormone preparation.. PubMed. 21. 537–44.8 indexed citations
19.
Yunoki, K. & A. Clark Griffin. (1960). Purification of toxohormone by column chromatography.. PubMed. 20. 533–40.18 indexed citations
20.
Yunoki, K., et al.. (1956). [Studies on the cancer toxin].. PubMed. 47(3-4). 306–8.1 indexed citations
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.