A more efficient method to generate integration-free human iPS cells
Impact in
- Molecular Biology 1.2k
Classified as
- Journal
- Nature Methods
In The Last Decade
doi.org/10.1038/nmeth.1591 →Countries where authors are citing A more efficient method to generate integration-free human iPS cells
This map shows the geographic impact of A more efficient method to generate integration-free human iPS cells. 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 A more efficient method to generate integration-free human iPS cells with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A more efficient method to generate integration-free human iPS cells more than expected).
Fields of papers citing A more efficient method to generate integration-free human iPS cells
This network shows the impact of A more efficient method to generate integration-free human iPS cells. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the A more efficient method to generate integration-free human iPS cells.
About A more efficient method to generate integration-free human iPS cells
This paper, published in 2011, received 1.4k indexed citations . Written by Keisuke Okita, Yasuko Matsumura, Yoshiko Sato, A. Okada, Asuka Morizane, Satoshi Okamoto, Hyenjong Hong, Masato Nakagawa, Koji Tanabe and Kenichi Tezuka covering the research area of Molecular Biology and Physiology. It is primarily cited by scholars working on Molecular Biology (1.2k citations), Cellular and Molecular Neuroscience (204 citations), Surgery (190 citations), Biomedical Engineering (184 citations) and Genetics (176 citations). Published in Nature Methods.
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/nmeth.1591.