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.
A novel fibrinolytic enzyme (nattokinase) in the vegetable cheese Natto; a typical and popular soybean food in the Japanese diet
1987466 citationsHirofumi Sumi, Hiroki Hamada et al.Cellular and Molecular Life Sciencesprofile →
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 H Mihara'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 H Mihara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites H Mihara more than expected).
This network shows the impact of papers produced by H Mihara. 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 H Mihara. The network helps show where H Mihara may publish in the future.
Co-authorship network of co-authors of H Mihara
This figure shows the co-authorship network connecting the top 25 collaborators of H Mihara.
A scholar is included among the top collaborators of H Mihara 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 H Mihara. H Mihara is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Matsuoka, Yasuo, Hiroshi Tsushima, Yasutoshi Koga, H Mihara, & V. K. Hopsu‐Havu. (1992). An inactive cathepsin B-like enzyme and cysteine proteinase inhibitors in colon cancer ascites.. PubMed. 39(2). 107–14.4 indexed citations
Mihara, H. (1991). [Fibrinolytic enzymes extracted from the earthworm. Lumbricus rubellus: a possible thrombolytic agent].. PubMed. 53(7). 231–43.5 indexed citations
Sumi, Hirofumi, Hiroki Hamada, Hiroshi Tsushima, H Mihara, & H Muraki. (1987). A novel fibrinolytic enzyme (nattokinase) in the vegetable cheese Natto; a typical and popular soybean food in the Japanese diet. Cellular and Molecular Life Sciences. 43(10). 1110–1111.466 indexed citations breakdown →
11.
Sumi, Hirofumi, et al.. (1985). Elastase digested urokinase. 41(12). 1546–1548.
12.
Mihara, H, et al.. (1984). [Mathematical simulation of the blood coagulation system].. PubMed. 46(4). 139–55.1 indexed citations
13.
Matsuo, Osamu, et al.. (1983). The role of plasminogen activator in ovulation.. PubMed. 33(2). 105–10.11 indexed citations
Sumi, Hirofumi, H Mihara, & Naotika Toki. (1981). [Purification and characterization of fibrin-binding urokinase (author's transl)].. PubMed. 44(5). 1044–9.
16.
Kosugi, Tomoki, et al.. (1981). Antiplasmin activity in carrageenin-induced inflammation of rats.. PubMed. 3(3-4). 173–6.2 indexed citations
17.
Sumi, Hirofumi, et al.. (1981). Human urinary trypsin inhibitors purified by affinity chromatography on trypsin-sepharose.. PubMed. 44(1). 146–53.9 indexed citations
Mihara, H, et al.. (1970). [Studies on the activation mechanism of fibrinolysis by dextran sulphate].. PubMed. 32(1). 25–34.1 indexed citations
20.
Kinjo, Kentaro, H Mihara, & Y Funahara. (1963). STUDIES ON THE FIBRINOLYSIS IN TUMOR BEARING MICE. II. APPEARANCE OF FIBRINOLYTIC ENZYME IN ASCITES AFTER TUMOR CELLS INOCULATION.. PubMed. 18. 161–7.1 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.