Kimiko Ubukata
- Epidemiology top 2%
- Infectious Diseases top 1%
- Molecular Medicine top 0.5%
- Molecular Biology top 10%
- Microbiology top 0.5%
- Co-authors
- M KonnoMichio MatsuhashiNaoko YamashitaSatoshi IwataNaoko ChibaShinichiro NakamuraHisahiro YoshidaMiyuki Morozumi
- Topics
- Pneumonia and Respiratory Infections (45 papers)Streptococcal Infections and Treatments (28 papers)Antimicrobial Resistance in Staphylococcus (27 papers)
- Partner nations
- JapanUnited StatesKenya
In The Last Decade
Kimiko Ubukata
83 papers receiving 2.9k citations
Peers
Comparison fields: 5 of 96
- Epidemiology 1.4k
- Infectious Diseases 1.2k
- Molecular Medicine 863
- Molecular Biology 738
- Microbiology 720
Countries citing papers authored by Kimiko Ubukata
This map shows the geographic impact of Kimiko Ubukata'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 Kimiko Ubukata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kimiko Ubukata more than expected).
Fields of papers citing papers by Kimiko Ubukata
This network shows the impact of papers produced by Kimiko Ubukata. 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 Kimiko Ubukata. The network helps show where Kimiko Ubukata may publish in the future.
Co-authorship network of co-authors of Kimiko Ubukata
This figure shows the co-authorship network connecting the top 25 collaborators of Kimiko Ubukata. A scholar is included among the top collaborators of Kimiko Ubukata 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 Kimiko Ubukata. Kimiko Ubukata is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 12 | |
| 4 | 13 | |
| 5 | 12 | |
| 6 | 1 | |
| 7 | 38 | |
| 8 | 17 | |
| 9 | 20 | |
| 10 | 4 | |
| 11 | 19 | |
| 12 | 11 | |
| 13 | 5 | |
| 14 | 2 | |
| 15 | 8 | |
| 16 | 47 | |
| 17 | Antibiotic susceptibility and T type identification of Streptococcus pyogenes isolated from pediatric outpatients with pharyngotonsillitis | 2 |
| 18 | 1 | |
| 19 | A case report of postoperative MRSA enterocolitis: Enzymatic detection of polymerase chain reaction for early diagnosis of MRSA | 1 |
| 20 | The norA gene conferring new quinolone resistance in staphylococcus epidermidis | 3 |
About Kimiko Ubukata
Kimiko Ubukata is a scholar working on Microbiology, Molecular Medicine and Infectious Diseases, having authored 85 papers that have together received 3.1k indexed citations. Recurring topics across this work include Pneumonia and Respiratory Infections (45 papers), Streptococcal Infections and Treatments (28 papers) and Antimicrobial Resistance in Staphylococcus (27 papers). The work is most often cited by research in Molecular Medicine (863 citations), Microbiology (720 citations) and Infectious Diseases (1.2k citations). Kimiko Ubukata has collaborated with scholars based in Japan, United States and Kenya. Frequent co-authors include M Konno, Michio Matsuhashi, Naoko Yamashita, Satoshi Iwata, Naoko Chiba, Shinichiro Nakamura, Hisahiro Yoshida, Miyuki Morozumi, M Bogaki and Keisuke Sunakawa. Their work appears in journals such as PLoS ONE, Journal of Bacteriology and Journal of Clinical Microbiology.
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.