Tumour evolution inferred by single-cell sequencing
Impact in
- Cancer Research 1.2k
- Molecular Biology 1.2k
Classified as
- Journal
- Nature
In The Last Decade
doi.org/10.1038/nature09807 →Countries where authors are citing Tumour evolution inferred by single-cell sequencing
This map shows the geographic impact of Tumour evolution inferred by single-cell sequencing. 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 Tumour evolution inferred by single-cell sequencing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tumour evolution inferred by single-cell sequencing more than expected).
Fields of papers citing Tumour evolution inferred by single-cell sequencing
This network shows the impact of Tumour evolution inferred by single-cell sequencing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Tumour evolution inferred by single-cell sequencing.
About Tumour evolution inferred by single-cell sequencing
This paper, published in 2011, received 2.1k indexed citations . Written by Nicholas E. Navin, Jude Kendall, Jennifer E. Troge, Peter Andrews, Linda Rodgers, Asya Stepansky, Dan L. Levy, Diane Esposito, Lakshmi B. Muthuswamy and A. Krasnitz covering the research area of Genetics, Molecular Biology and Cancer Research. It is primarily cited by scholars working on Cancer Research (1.2k citations), Molecular Biology (1.2k citations), Oncology (588 citations), Genetics (268 citations) and Pulmonary and Respiratory Medicine (218 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/nature09807.