Kazushi Iwata
- Cancer Research top 0.5%
- Oncology top 2%
- Molecular Biology top 10%
- Hematology top 2%
- Rheumatology top 2%
- Co-authors
- Taro HayakawaYasunori OkadaKyoko YamashitaNoboru FujimotoIsao NakanishiKazuhito NakaHideaki NagaseK. Tomita
- Topics
- Protease and Inhibitor Mechanisms (37 papers)Peptidase Inhibition and Analysis (24 papers)Blood Coagulation and Thrombosis Mechanisms (11 papers)
- Partner nations
- JapanUnited StatesSpain
In The Last Decade
Kazushi Iwata
85 papers receiving 3.6k citations
Peers
Comparison fields: 5 of 120
- Cancer Research 1.9k
- Oncology 1.1k
- Molecular Biology 977
- Hematology 620
- Rheumatology 490
Countries citing papers authored by Kazushi Iwata
This map shows the geographic impact of Kazushi Iwata'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 Kazushi Iwata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kazushi Iwata more than expected).
Fields of papers citing papers by Kazushi Iwata
This network shows the impact of papers produced by Kazushi Iwata. 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 Kazushi Iwata. The network helps show where Kazushi Iwata may publish in the future.
Co-authorship network of co-authors of Kazushi Iwata
This figure shows the co-authorship network connecting the top 25 collaborators of Kazushi Iwata. A scholar is included among the top collaborators of Kazushi Iwata 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 Kazushi Iwata. Kazushi Iwata is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 5 | |
| 3 | One-step Sandwich Enzyme Immunoassays for Human Matrix Metalloproteinase 13(Collagenase-3)using Monoclonal Antibodies | 9 |
| 4 | A one-step monoclonal antibody-based sandwich enzyme immunoassay for human active matrilysin (MMP-7) and its complexes with TIMP-1 and TIMP-2 | 3 |
| 5 | 49 | |
| 6 | 147 | |
| 7 | 159 | |
| 8 | 11 | |
| 9 | 2 | |
| 10 | Studies on glycoprotein toxins produced by a Candida albicans strain. II. Limulus amoebocyte lysate-gelling activity of one of the GP toxins and the cellular mannan isolated from the same strain. | 2 |
| 11 | 2 | |
| 12 | 2 | |
| 13 | 12 | |
| 14 | 12 | |
| 15 | 10 | |
| 16 | 20 | |
| 17 | 30 | |
| 18 | 10 | |
| 19 | 2 | |
| 20 | 5 |
About Kazushi Iwata
Kazushi Iwata is a scholar working on Cancer Research, Immunology and Allergy and Hematology, having authored 86 papers that have together received 3.7k indexed citations. Recurring topics across this work include Protease and Inhibitor Mechanisms (37 papers), Peptidase Inhibition and Analysis (24 papers) and Blood Coagulation and Thrombosis Mechanisms (11 papers). The work is most often cited by research in Cancer Research (1.9k citations), Immunology and Allergy (420 citations) and Hematology (620 citations). Kazushi Iwata has collaborated with scholars based in Japan, United States and Spain. Frequent co-authors include Taro Hayakawa, Yasunori Okada, Kyoko Yamashita, Noboru Fujimoto, Isao Nakanishi, Kazuhito Naka, Hideaki Nagase, K. Tomita, Takashi Shinya and Suneel Apte. Their work appears in journals such as Journal of Biological Chemistry, The Journal of Immunology and Biochemical 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.