Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion
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doi.org/10.1038/nature19084 →Countries where authors are citing Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion
This map shows the geographic impact of Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion. 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 Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion more than expected).
Fields of papers citing Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion
This network shows the impact of Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion.
About Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion
This paper, published in 2016, received 813 indexed citations . Written by Cristovão M. Sousa, Douglas E. Biancur, Xiaoxu Wang, Christopher J. Halbrook, Mara H. Sherman, Li Zhang, Daniel M. Kremer, Rosa F. Hwang, Haoqiang Ying and John M. Asara covering the research area of Oncology and Surgery. It is primarily cited by scholars working on Molecular Biology (474 citations), Cancer Research (383 citations) and Oncology (313 citations). Published in Nature.
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/10.1038/nature19084.