Gene-expression profiles predict survival of patients with lung adenocarcinoma
Impact in
- Molecular Biology 1.1k
- Cancer Research 417
Classified as
- Journal
- Nature Medicine
In The Last Decade
doi.org/10.1038/nm733 →Countries where authors are citing Gene-expression profiles predict survival of patients with lung adenocarcinoma
This map shows the geographic impact of Gene-expression profiles predict survival of patients with lung adenocarcinoma. 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 Gene-expression profiles predict survival of patients with lung adenocarcinoma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gene-expression profiles predict survival of patients with lung adenocarcinoma more than expected).
Fields of papers citing Gene-expression profiles predict survival of patients with lung adenocarcinoma
This network shows the impact of Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Gene-expression profiles predict survival of patients with lung adenocarcinoma.
About Gene-expression profiles predict survival of patients with lung adenocarcinoma
This paper, published in 2002, received 1.5k indexed citations . Written by David G. Beer, Sharon L. R. Kardia, Chiang‐Ching Huang, Thomas J. Giordano, Albert M. Levin, David E. Misek, Lin Lin, Guoan Chen, Tarek G. Gharib and Dafydd G. Thomas covering the research area of Molecular Biology and Pulmonary and Respiratory Medicine. It is primarily cited by scholars working on Molecular Biology (1.1k citations), Cancer Research (417 citations), Pulmonary and Respiratory Medicine (403 citations), Oncology (265 citations) and Artificial Intelligence (141 citations). Published in Nature Medicine.
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/nm733.