MicroRNA-21 targets tumor suppressor genes in invasion and metastasis
Impact in
- Cancer Research 561
Classified as
- Authors
- ZhuHailong HailongWuShijieSheng
- Journal
- 细胞研究：英文版
In The Last Decade
doi.org/w8223602 →Countries where authors are citing MicroRNA-21 targets tumor suppressor genes in invasion and metastasis
This map shows the geographic impact of MicroRNA-21 targets tumor suppressor genes in invasion and metastasis. 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 MicroRNA-21 targets tumor suppressor genes in invasion and metastasis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites MicroRNA-21 targets tumor suppressor genes in invasion and metastasis more than expected).
Fields of papers citing MicroRNA-21 targets tumor suppressor genes in invasion and metastasis
This network shows the impact of MicroRNA-21 targets tumor suppressor genes in invasion and metastasis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the MicroRNA-21 targets tumor suppressor genes in invasion and metastasis.
About MicroRNA-21 targets tumor suppressor genes in invasion and metastasis
This paper, published in 2008, received 721 indexed citations . Written by Zhu, Hailong Hailong, Wu, Shijie, Sheng and Mo Mo covering the research area of Cancer Research and Molecular Biology. It is primarily cited by scholars working on Cancer Research (561 citations), Molecular Biology (534 citations), Oncology (38 citations), Immunology (19 citations) and Pathology and Forensic Medicine (15 citations). Published in 细胞研究：英文版.
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.
This paper is also available at doi.org/w8223602.