Massively parallel single-nucleus RNA-seq with DroNc-seq
Impact in
- Cancer Research 119
Classified as
- Journal
- Nature Methods
In The Last Decade
doi.org/10.1038/nmeth.4407 →Countries where authors are citing Massively parallel single-nucleus RNA-seq with DroNc-seq
This map shows the geographic impact of Massively parallel single-nucleus RNA-seq with DroNc-seq. 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 Massively parallel single-nucleus RNA-seq with DroNc-seq with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massively parallel single-nucleus RNA-seq with DroNc-seq more than expected).
Fields of papers citing Massively parallel single-nucleus RNA-seq with DroNc-seq
This network shows the impact of Massively parallel single-nucleus RNA-seq with DroNc-seq. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Massively parallel single-nucleus RNA-seq with DroNc-seq.
About Massively parallel single-nucleus RNA-seq with DroNc-seq
This paper, published in 2017, received 645 indexed citations . Written by Naomi Habib, Inbal Avraham‐Davidi, Anindita Basu, Tyler Burks, Karthik Shekhar, Matan Hofree, Sourav Choudhury, François Aguet, Ellen Gelfand and Kristin Ardlie covering the research area of Molecular Biology and Cancer Research. It is primarily cited by scholars working on Molecular Biology (473 citations), Cancer Research (119 citations), Neurology (115 citations), Immunology (92 citations) and Genetics (45 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.4407.