Simultaneous epitope and transcriptome measurement in single cells
Impact in
- Molecular Biology 1.4k
- Immunology 551
Classified as
- Authors
- Marlon StoeckiusChristoph HafemeisterWilliam StephensonBrian Houck‐LoomisPratip K. Chattopadhyay
- Journal
- Nature Methods
In The Last Decade
doi.org/10.1038/nmeth.4380 →Countries where authors are citing Simultaneous epitope and transcriptome measurement in single cells
This map shows the geographic impact of Simultaneous epitope and transcriptome measurement in single 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 Simultaneous epitope and transcriptome measurement in single cells with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simultaneous epitope and transcriptome measurement in single cells more than expected).
Fields of papers citing Simultaneous epitope and transcriptome measurement in single cells
This network shows the impact of Simultaneous epitope and transcriptome measurement in single cells. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Simultaneous epitope and transcriptome measurement in single cells.
About Simultaneous epitope and transcriptome measurement in single cells
This paper, published in 2017, received 1.9k indexed citations . Written by Marlon Stoeckius, Christoph Hafemeister, William Stephenson, Brian Houck‐Loomis, Pratip K. Chattopadhyay, Harold Swerdlow and Peter Smibert covering the research area of Molecular Biology and Immunology. It is primarily cited by scholars working on Molecular Biology (1.4k citations), Immunology (551 citations), Cancer Research (273 citations), Oncology (251 citations) and Biophysics (238 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.4380.