Countries where authors publish in Translational Oncology
Since Specialization
Citations
This map shows the geographic impact of research published in Translational Oncology. 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 papers published in Translational Oncology with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Translational Oncology more than expected).
Fields of papers published in Translational Oncology
This network shows the impact of papers published in Translational Oncology. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Translational Oncology.
About Translational Oncology
The 2.6k papers published in Translational Oncology in the last decades have received a total of 47.1k indexed citations . Papers published in Translational Oncology usually cover Cancer Research (762 papers), Oncology (1.0k papers) and Pulmonary and Respiratory Medicine (678 papers) specifically the topics of RNA modifications and cancer (222 papers), Cancer-related molecular mechanisms research (221 papers), Cancer Immunotherapy and Biomarkers (219 papers), Cancer Cells and Metastasis (173 papers), Cancer Genomics and Diagnostics (172 papers), Ferroptosis and cancer prognosis (170 papers), MicroRNA in disease regulation (165 papers) and Cancer, Hypoxia, and Metabolism (165 papers). The most active scholars publishing in Translational Oncology are Pengfei Xu, Yue Xi, Doménico Ribatti, Roberto Tamma, Tiziana Annese, Xiaosheng Wang, Zhixian Liu, Xiaoqi Liu, Yi Sun and Qingrong Sun.
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.