Countries where authors publish in Cell Death Discovery
Since Specialization
Citations
This map shows the geographic impact of research published in Cell Death Discovery. 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 Cell Death Discovery with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cell Death Discovery more than expected).
Fields of papers published in Cell Death Discovery
This network shows the impact of papers published in Cell Death Discovery. 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 Cell Death Discovery.
About Cell Death Discovery
The 3.0k papers published in Cell Death Discovery in the last decades have received a total of 56.3k indexed citations . Papers published in Cell Death Discovery usually cover Cancer Research (799 papers), Molecular Biology (2.0k papers), Immunology (476 papers), Oncology (457 papers) and Cell Biology (284 papers) specifically the topics of RNA modifications and cancer (383 papers), Cancer-related molecular mechanisms research (360 papers), Autophagy in Disease and Therapy (243 papers), MicroRNA in disease regulation (222 papers), Ferroptosis and cancer prognosis (221 papers), Epigenetics and DNA Methylation (195 papers), Circular RNAs in diseases (184 papers) and Ubiquitin and proteasome pathways (169 papers). The most active scholars publishing in Cell Death Discovery are Mingxia Jiang, Lisha Li, Yanjing Li, Ling Qi, Zhong Guo, Gerry Melino, John H. Kehrl, Chong-Shan Shi, Hongbo Qi and Qinjin Dai.
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.