Seishi Murakami
- Molecular Biology top 2%
- Epidemiology top 0.5%
- Hepatology top 0.5%
- Cancer Research top 2%
- Immunology top 5%
- Co-authors
- Shuichi KanekoKenichi KobayashiYong LinNaoki OishiTatsuya YamashitaMin YiHong TangMasao Honda
- Topics
- Hepatitis B Virus Studies (41 papers)Hepatitis C virus research (33 papers)RNA Interference and Gene Delivery (12 papers)
- Cited by
- HepatologyEpidemiologyAging
- Partner nations
- JapanUnited StatesChina
In The Last Decade
Seishi Murakami
94 papers receiving 5.4k citations
Peers
Comparison fields: 5 of 102
- Molecular Biology 2.6k
- Epidemiology 2.5k
- Hepatology 1.9k
- Cancer Research 705
- Immunology 692
Countries citing papers authored by Seishi Murakami
This map shows the geographic impact of Seishi Murakami'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 Seishi Murakami with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seishi Murakami more than expected).
Fields of papers citing papers by Seishi Murakami
This network shows the impact of papers produced by Seishi Murakami. 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 Seishi Murakami. The network helps show where Seishi Murakami may publish in the future.
Co-authorship network of co-authors of Seishi Murakami
This figure shows the co-authorship network connecting the top 25 collaborators of Seishi Murakami. A scholar is included among the top collaborators of Seishi Murakami 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 Seishi Murakami. Seishi Murakami is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 27 | |
| 2 | 10 | |
| 3 | 28 | |
| 4 | Telomerase maintains telomere structure in normal human cells | 422 |
| 5 | The transcriptional transactivation function of HBx protein is important for its augmentation role in hepatitis B virus replication1 | 160 |
| 6 | Nucleolin interacts with telomerase | 95 |
| 7 | 235 | |
| 8 | Two independent regions of human telomerase reverse transcriptase (hTERT) are important for its oligomerization and telomerase activity | 7 |
| 9 | Oligomeric interacion of Hepatitis C Virus NS5B is critical for catalytic activity of RNA dependent RNA polymerase | 11 |
| 10 | Hepatitis C Virus NS5A Binds RNA-Dependent RNA polymerase NS5B and modulates RdRP activity | 3 |
| 11 | 29 | |
| 12 | 87 | |
| 13 | 123 | |
| 14 | 193 | |
| 15 | 42 | |
| 16 | 33 | |
| 17 | 5 | |
| 18 | 16 | |
| 19 | 26 | |
| 20 | 3 |
About Seishi Murakami
Seishi Murakami is a scholar working on Hepatology, Aging and Epidemiology, having authored 96 papers that have together received 5.5k indexed citations. Recurring topics across this work include Hepatitis B Virus Studies (41 papers), Hepatitis C virus research (33 papers) and RNA Interference and Gene Delivery (12 papers). The work is most often cited by research in Hepatology (1.9k citations), Epidemiology (2.5k citations) and Aging (98 citations). Seishi Murakami has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Shuichi Kaneko, Kenichi Kobayashi, Yong Lin, Shuichi Kaneko, Naoki Oishi, Tatsuya Yamashita, Min Yi, Hong Tang, Masao Honda and Dorjbal Dorjsuren. Their work appears in journals such as Nature, Journal of Biological Chemistry 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.